International Conference on Computer Vision

NEXT EVENT SESSION
27-28 December 2023 (Instant E-Certificate)
For Enquiries:
computer@scifat.com

Next Webinar Conference Session starts in

About the Conference

Introduction of the conferences

Computer Vision conferences organized by ScienceFather group. ScienceFather takes the privilege to invite speakers, participants, students, delegates, and exhibitors from across the globe to its International Conference on computer vision conferences to be held in the Various Beautiful cites of the world. computer vision conferences are a discussion of common Inventions-related issues and additionally trade information, share proof, thoughts, and insight into advanced developments in the science inventions service system. New technology may create many materials and devices with a vast range of applications, such as in Science, medicine, electronics, biomaterials, energy production, and consumer products. The focal point of computer vision is to bring forward discoveries, examine the system and strategic issues, assemble and keep forth basic strategies between analysts, professionals, arrangement producers, and agents of science Associations. Essential Computer vision conferences emphasize its theme "Innovation through Information on Computer vision" and intends to provide an impetus to practice, administration, and training in connection to Computer vision inconsistencies and conjugation of other different points. Computer vision conferences are an opportunity to interact with specialists and learn the latest new science inventions information. The meeting will be organized to bring together practitioners, administrators, policymakers, politicians, and researchers within the field of Computer vision .

Theme: Exploring the Recent research and Advancements in Computer vision

2nd Edition of  Computer Vision | 23-26 June 2023 | San Francisco, United States (Hybrid)

3rd Edition of  Computer Vision | 27-28 July 2023 | Delhi, India (Hybrid)

4th Edition of  Computer Vision | 24-25 August 2023 | Berlin, Germany (Hybrid)

5th Edition of  Computer Vision | 24-25 September 2023 | Mumbai, India( Hybrid)

6th Edition of  Computer Vision | 19-20 October 2023 | Paris, France (Hybrid)

7th Edition of  Computer Vision | 26-27 November 2023 | Agra, India (Hybrid)

8th Edition of  Computer Vision | 07-08 December 2023 | Dubai, United Arab Emirates (Hybrid)

Call for paper

Call for Abstract/paper

Original Articles/papers are invited from Industry Persons, Scientist, Academician, Research Scholars, P.G. & U.G. Students for presentation in our International Computer vision Conference. All articles/papers must be in MS-Word (.doc or .docx) format, including the title, author's name, an affiliation of all authors, e-mail, abstract, keywords, Conclusion, Acknowledgment, and References.

Submit Abstract

The Candidates with eligibility can click the "Submit Paper/Abstract Now" button and fill up the online submission form and Submit.

Abstract/Full Paper submission

Final/Full Paper submission is optional: If you don't want your abstract/full paper to be published in the Conference Abstracts & Proceedings CD (with ISBN number) and only want to present it at the conference, it is acceptable.

Page limit: There is a limit of 6-8 pages for a final/full paper. An additional page is chargeable.

Paper language: Final/Full papers should be in English.

Templates: "Final paper template," "Final abstract template"

All the final papers should be uploaded to the website online system according to "The final paper template" as word doc. Or Docx, since this will be the camera-ready published version. Please note that final papers that are not uploaded to online System as a word doc./docx after the opening of final paper submissions according to the template above will not be published in the CONFERENCE Abstracts & Proceedings CD (with ISBN)

Journal Publication

Journal Publication

Computer vision Conferences All accepted papers will be included in the conference proceedings, which will be recommended in one of the author's prescribed ScienceFather International journals.

Registration

Registration Procedure

  • Click the “Register Now” button on the conference page and enter your Submission ID in the Search Box
  • Your Submissions will be listed on that page. You can find the Register Now link beside your submission. Click the link, and now you will be redirected to the Conference registration form where you can make your registration using credit/debit cards.
  • The Fee charged for E-Poster is to display the E-Posters only on the Website. The Abstract will be published in the conference proceeding book.

Registration Types

Speaker Registration

  • Access to all event Session
  • Certificate of Presentation
  • Handbook
  • Conference Kit
  • Tea, Coffee & Snack,
  • Lunch during the Conference
  • Publication of Abstract /Full Paper at the Conference Proceedings Book
  • Opportunity to give a Keynote/ Poster Presentations/ Plenary/ Workshop
  • Opportunity to publish your Abstract in any of our esteemed Journals discounted rate
  • Opportunity to publish your full article in our open access book at a discounted rate
  • One to One Expert Forums

Delegate (Participant) Registration

  • Access to all Event Sessions
  • Participation Certificate
  • Handbook
  • Conference Kit
  • Tea, Coffee & Snack,
  • Lunch during the Conference
  • Delegates are not allowed to present

Poster Registration

  • Includes all the above Registration Benefits
  • You will have to bring your Posters to the Conference Venue
  • Best poster award memento and certificate on stage.

Poster Guidelines

  • The poster should be 1×1 m Size.
  • The title, contents, text, and the author’s information should be visible.
  • Present numerical data in the form of graphs rather than tables.
  • Figures make trends in the data much more evident.
  • Avoid submitting high word-count posters.
  • Poster contains, e.g., Introduction, Methods, Results, Discussion, Conclusions, and Literature.

Research Forum (Awards)

  • Includes all the above Registration Benefits.
  • The attendee should be required age limit.
  • Award memento and certificate on stage.

E-Poster Presentation

  • The amount charged for E-Posters is to display the E-Posters only on the website
  • The presenter will get an e-poster participation certificate as a soft copy
  • The abstract will be published in the particular journal and also in the conference proceeding book
  • The presenter is not required to be present in person at the Conference

Video Presentation

  • The amount charged for Video Presentation is to display the Presentation at the Conference.
  • The presenter will get Video participation certificate as a soft copy
  • The abstract will be published in the particular journal and also in the conference proceeding book
  • The presenter is not required to be present in person at the Conference

Accompanying Person

  • Accompanying Persons attend the participants at the Conference who may be either a spouse/family partner or a son/daughter and must register under this category.
  • Please note that business partners do not qualify as Accompanying Persons and cannot register as an Accompanying Person.

Committee Members

Committee Members

TitleFirst NameLast NameInstitution/OrganizationCountry
MrWasieAbuhayUniversity of GondarEthiopia
Prof DrTamene AdugnaDemissieJimma UniversityEthiopia
MrAshenafiManayeTigray Institute of Policy StudiesEthiopia
MrAshenafi BelihuTadesseArba Minch UniversityEthiopia
Assoc Prof DrSohaElmasryfaculty oof pharmacy damanhour universityEgypt
DrVijayalakshmiVErode Sengunthar Engineering CollegeIndia
ProfElifOZYILMAZSelcuk UniversityTurkey
MrWahidurRahmanUttara University, Dhaka, BangladeshBangladesh
DrpoorniammalrajendranTamil Nadu Agricultural UniversityIndia
ProfNiannianWangZhengzhou UniversityChina
DrAhmed UddinShenzhen UniversityChina
DrEdliraMucaUniversity of TurinItaly
DrQiuDefuSchool of Information and Control EngineeringChina
MrPranabKarIndian Institute of Technology GuwahatiIndia
DrFatiqaZafarUniversity of Sahiwal, SahiwalPakistan
DrDengyunXuJilin UniversityChina
TitleFirst NameLast NameInstitution/OrganizationCountry

Conference Awards

Details of Conference Awards

Sciencefather awards Researchers and Research organizations around the world with the motive of Encouraging and Honoring them for their Significant contributions & Achievements for the Advancement in their field of expertise. Researchers and scholars of all nationalities are eligible to receive Sciencefather Research awards. Nominees are judged on past accomplishments, research excellence, and outstanding academic achievements.

Award Categories

Best Poster Award

Posters will be evaluated based on Presentation Style, Research Quality, and Layout/Design. Unique opportunity to combine visual and oral explanations of your projects in the form of poster presentation. Posters should have the Title (with authors affiliation & contact details), Introduction, Methods, Results (with tables, graphs, pictures), Discussion, Conclusion, References, and Acknowledgements. The size of the poster should be: 1mX1.5m; Text:16-26 pt; Headings: 32-50 pt; Title: 70 pt; Color: Preferable. Bring your poster to the meeting, using tubular packaging and presenting duration: 10 min discussion & 5 min query per person. Eligibility: The presenter can nominate the Award. He must be under 40 years of age as on the conference date.

Best Presentation Award

The presentation will be evaluated based on Presentation Style, Research Quality, and Layout/Design. Unique opportunity to combine visual and oral explanations of your projects in the form of poster presentations. The presentation should have the Title (with authors affiliation & contact details), Introduction, Methods, Results (with tables, graphs, pictures), Discussion, Conclusion, References, and Acknowledgements. Bring your presentation to the meeting, using a pen drive, presenting duration: 10-20 min discussion & 5 min query per person. Eligibility: The presenter can nominate the Award. He must be under 55 years of age as of the conference date.

Best Paper Award

Paper will be evaluated based on Format, Research Quality, and Layout/Design. The paper should have the Title (with authors affiliation & contact details), Introduction, Methods, Results (with tables, graphs, pictures), Discussion, Conclusion, References, and Acknowledgements. Eligibility: The presenter can nominate the Award. He must be under 55 years of age as of the conference date.

Instructions

Instructions for submission

If you want to submit only your Abstract

  • If you want to publish only your abstract (it is also optional) in the CONFERENCE Abstracts & Proceedings CD (with ISBN), upload your abstract again according to the Final abstract template as a word doc. Or Docx.
  • If you also don't want your abstract to be published in the CONFERENCE Abstracts & Proceedings CD (with an ISBN) and only want to present it at the conference, it is also acceptable.

How to Submit your Abstract / Full Paper

Please read the instructions below then submit your Abstract/ Full Paper (or just final abstract) via the online conference system:

  • STEP 1: Please download the Abstract /Final Paper Template and submit your final paper strictly according to the template: Computer vision App Conference Final paper template in word format (.doc /.docx). See a Final abstract template formatted according to the template.
  • STEP 2: Please ensure that the Abstract/ full paper follows exactly the format and template described in the final paper template document below since this will be the camera-ready published version. All last articles should be written only in English and "word document" as .doc or .docx.
  • STEP 3: You can submit your final paper(s) to the online conference system only by uploading/ Re-submission your current submission.
  • STEP 4: After logging/using submission ID in the online conference system, click on the "Re-submission" link at the bottom of the page.
  • STEP 5: After the "Re submission page" opens, upload your abstract/ final paper (it should be MS word document -doc. or Docx-).

General Information

  • Dress Code: Participants have to wear a formal dress. There are no restrictions on color or design. The audience attending only the ceremony can wear clothing of their own choice.
  • Certificate Distribution: Each presenter's name will be called & asked to collect their certificate on the Stage with an official photographer to capture the moments.

Terms & Conditions

ScienceFather Terms & Conditions

Computer vision Conferences Terms & Conditions Policy was last updated on June 25, 2022.

Privacy Policy

Computer vision conferences customer personal information for our legitimate business purposes, process and respond to inquiries, and provide our services, to manage our relationship with editors, authors, institutional clients, service providers, and other business contacts, to market our services and subscription management. We do not sell, rent/ trade your personal information to third parties.

Relationship

Computer vision Conferences Operates a Customer Association Management and email list program, which we use to inform customers and other contacts about our services, including our publications and events. Such marketing messages may contain tracking technologies to track subscriber activity relating to engagement, demographics, and other data and build subscriber profiles.

Disclaimer

All editorial matter published on this website represents the authors' opinions and not necessarily those of the Publisher with the publications. Statements and opinions expressed do not represent the official policies of the relevant Associations unless so stated. Every effort has been made to ensure the accuracy of the material that appears on this website. Please ignore, however, that some errors may occur.

Responsibility

Delegates are personally responsible for their belongings at the venue. The Organizers will not be held accountable for any stolen or missing items belonging to Delegates, Speakers, or Attendees; due to any reason whatsoever.

Insurance

Computer vision conferences Registration fees do not include insurance of any kind.

Press and Media

Press permission must be obtained from the Computer vision conferences Organizing Committee before the event. The press will not quote speakers or delegates unless they have obtained their approval in writing. This conference is not associated with any commercial meeting company.

Transportation

Computer vision Conferences Please note that any (or) all traffic and parking is the registrant's responsibility.

Requesting an Invitation Letter

Computer vision Conferences For security purposes, the invitation letter will be sent only to those who had registered for the conference. Once your registration is complete, please contact computer@scifat.com to request a personalized letter of invitation.

Cancellation Policy

If Computer vision Conferences cancels this event, you will receive a credit for 100% of the registration fee paid. You may use this credit for another Computer vision Conferences event, which must occur within one year from the cancellation date.

Postponement Policy

Suppose Computer vision Conferences postpones an event for any reason and you are unable or indisposed to attend on rescheduled dates. In that case, you will receive a credit for 100% of the registration fee paid. You may use this credit for another Computer vision Conferences, which must occur within one year from the date of postponement.

Transfer of registration

Computer vision Conferences All fully paid registrations are transferable to other persons from the same organization if the registered person is unable to attend the event. The registered person must make transfers in writing to computer@scifat.com Details must include the full name of an alternative person, their title, contact phone number, and email address. All other registration details will be assigned to the new person unless otherwise specified. Registration can be transferred to one conference to another conference of ScienceFather if the person cannot attend one of the meetings. However, Registration cannot be transferred if it will be intimated within 14 days of the particular conference. The transferred registrations will not be eligible for Refund.

Visa Information

Computer vision Conferences Keeping given increased security measures, we would like to request all the participants to apply for Visa as soon as possible. ScienceFather will not directly contact embassies and consulates on behalf of visa applicants. All delegates or invitees should apply for Business Visa only. Important note for failed visa applications: Visa issues cannot come under the consideration of the cancellation policy of ScienceFather including the inability to obtain a visa.

Refund Policy

Computer vision Conferences Regarding refunds, all bank charges will be for the registrant's account. All cancellations or modifications of registration must make in writing to iot@sciencefather.com

If the registrant is unable to attend and is not in a position to transfer his/her participation to another person or event, then the following refund arrangements apply:

Keeping given advance payments towards Venue, Printing, Shipping, Hotels and other overheads, we had to keep Refund Policy is as following conditions,

  • Before 60 days of the Conference: Eligible for Full Refund less $100 Service Fee
  • Within 60-30 days of Conference: Eligible for 50% of payment Refund
  • Within 30 days of Conference: Not eligible for Refund
  • E-Poster Payments will not be refunded.

Accommodation Cancellation Policy

Computer vision Conferences Accommodation Providers such as hotels have their cancellation policies, and they generally apply when cancellations are made less than 30 days before arrival. Please contact us as soon as possible if you wish to cancel or amend your accommodation. ScienceFather will advise your accommodation provider's cancellation policy before withdrawing or changing your booking to ensure you are fully aware of any non-refundable deposits.

Sponsorship

Sponsorship Details

Computer vision Conferences warmly invite you to sponsor or exhibit of International Conference. We expect participants more than 200 numbers for our International conference will provide an opportunity to hear and meet/ads to Researchers, Practitioners, and Business Professionals to share expertise, foster collaborations, and assess rising innovations across the world in the core area of mechanical engineering.

Diamond Sponsorship

  1. Acknowledgment during the opening of the conference
  2. Complimentary Booth of size 10 meters square
  3. Four (4) delegate’s complimentary registrations with lunch
  4. Include marketing document in the delegate pack
  5. Logo on Conference website, Banners, Backdrop, and conference proceedings
  6. One exhibition stand (1×1 meters) for the conference
  7. One full cover page size ad in conference proceedings
  8. Opportunities for Short speech at events
  9. Option to sponsors conference kit
  10. Opportunity to sponsors conference lanyards, ID cards
  11. Opportunity to sponsors conference lunch
  12. Recognition in video ads
  13. 150-word company profile and contact details in the delegate pack

Platinum Sponsorship

  1. Three (3) delegate’s complimentary registrations with lunch
  2. Recognition in video ads
  3. Opportunity to sponsors conference lunch
  4. Opportunity to sponsors conference lanyards, ID cards
  5. Opportunity to sponsors conference kit
  6. Opportunity for Short speech at events
  7. One full-page size ad in conference proceedings
  8. One exhibition stand (1×1 meters) for the conference
  9. Logo on Conference website, Banners, Backdrop, and conference proceedings
  10. Include marketing document in the delegate pack
  11. Complimentary Booth of size 10 meters square
  12. Acknowledgment during the opening of the conference
  13. 100-word company profile and contact details in the delegate pack

Gold Sponsorship

  1. Two (2) delegate’s complimentary registrations with lunch
  2. Opportunities for Short speech at events
  3. Logo on Conference website, Banners, Backdrop, and conference proceedings
  4. Include marketing document in the delegate pack
  5. Complimentary Booth of size 10 meters square
  6. Acknowledgment during the opening of the conference
  7. 100-word company profile and contact details in the delegate pack
  8. ½ page size ad in conference proceedings

Silver Sponsorship

  1. Acknowledgment during the opening of the conference
  2. One(1) delegate’s complimentary registrations with lunch
  3. Include marketing document in the delegate pack
  4. Logo on Conference website, Banners, Backdrop, and conference proceedings
  5. ¼ page size ad in conference proceedings
  6. 100-word company profile and contact details in the delegate pack

Individual Sponsorship

  1. Acknowledgment during the opening of the conference
  2. One(1) delegate’s complimentary registrations with lunch

Registration Fees

Details Registration fees
Diamond Sponsorship USD 2999
Platinum Sponsorship USD 2499
Gold Sponsorship USD 1999
Silver Sponsorship USD 1499
Individual Sponsorship USD 999

Exhibitions

Exhibitions Details

Exhibit your Products & Services

Exhibit your Products & Services At Computer vision Conferences. Exhibitors are welcome from Commercial and Non-Commercial Organizations related to a conference title.

  • The best platform to develop new partnerships & collaborations.
  • Best location to speed up your route into every territory in the World.
  • Our exhibitor booths were visited 4-5 times by 80% of the attendees during the conference.
  • Network development with both Academia and Business.

Exhibitor Benefits

  • Exhibit booth of Size-3X3 sqm.
  • Promotion of your logo/Company Name/Brand Name through the conference website.
  • Promotional video on company products during the conference (Post session and Breaks).
  • Logo recognition in the Scientific program, Conference banner, and flyer.
  • One A4 flyer inserts into the conference kit.
  • An opportunity to sponsor 1 Poster Presentation Award.

Session Tracks

Conference Session Tracks

Object Detection and Recognition | Image Processing and Enhancement | Computer Vision for Robotics and Autonomous Systems | 3D Computer Vision | Medical Image Analysis | Video Analysis and Understanding | Deep Learning for Computer Vision | Applications of Computer Vision | Human-Computer Interaction| Biometrics and Security | Deep Metric Learning | Machine Learning for Computer Vision | Vision and Language | Computational Photography | Generative Models for Computer Vision | Visual SLAM | Biomedical and Healthcare Applications | Action Recognition | Face Recognition and Analysis | Augmented Reality (AR) and Virtual Reality (VR) | Surveillance and Security | Remote Sensing and Satellite Imagery Analysis | Industrial and Manufacturing Applications | Ethical and Social Implications | Multi-modal and Cross-modal Vision | Scene Understanding and Semantic Segmentation | Low-Level Vision | Big Data and Large-Scale Vision | Benchmark Datasets and Evaluation Methods | Hardware and Acceleration for Computer Vision | AI in Art and Creativity | Education and Outreach in Computer Vision | Startups and Industry Applications | Challenges and Competitions | Emerging Trends and Future Directions | Gesture and Pose Recognition | Image and Video Retrieval | Human Pose Estimation | Multi-Object Tracking | Document Image Analysis | Traffic and Transportation Analysis

 

Target Countries

Target Countries

    • EU
    • Switzerland
    • United States
    • China
    • Brazil
    • Canada
    • Japan
    • Russia
    • Australia

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Secure Multi-party Computation Protocol for Privacy-Preserving Data Analysis, Laura Martinez, ETH Zurich, Switzerland, EP98765432, 2018 | 9. Optical Computing Architecture for High-Speed Data Processing,Hiroshi Yamamoto, University of Tokyo, Japan, JP56789012, 2017 | 10. Enhanced Natural Language Understanding System using Deep Learning Techniques, Sophia Johnson, Harvard University, United States, US45678901, 2019 | 11. Neuromorphic Computing System for Efficient Pattern Recognition, Thomas Anderson, University of Cambridge, United Kingdom, UK76543210, 2020 | 12. Secure Homomorphic Encryption Scheme for Outsourced Data Processing, Emily Chen, Carnegie Mellon University, United States, US56789012, 2018 | 13. Virtual Reality Interface for Immersive Gaming Experience, Luca Rossi, Politecnico di Milano, Italy, IT12345678, 2017 | 14. Machine Learning Algorithm for Sentiment Analysis in Social Media, Amanda Wilson, University of Toronto, Canada, CA87654321, 2019 | 15. 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Augmented Reality System for Surgical Navigation and Visualization, Alejandro Ramirez, Massachusetts General Hospital, United States, US90123456, 2018 | 22. Optimization Algorithm for Energy-Efficient Task Scheduling in Cloud Computing, Mei Ling, National University of Singapore, Singapore, SG67890123, 2020 | 23. Secure Two-Factor Authentication System using Biometrics and Cryptography, Ahmed Khan, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, SA12345678, 2017 | 24. Computer Vision-Based Object Recognition System for Autonomous Vehicles, Sophia Lee, Stanford University, United States, US78901234, 2020 | 25. Efficient Data Mining Algorithm for Large-Scale Social Network Analysis, Antonio Gonzalez, University of Barcelona, Spain, ES23456789, 2018 | 26. Artificial Intelligence-Based Speech Recognition System for Voice Assistants, Emily Wilson, University of California, Berkeley, United States, US90123456, 2019 | 27. Secure Data Outsourcing Protocol for Cloud Storage, Chen Wei, Zhejiang University, China, CN34567890, 2021 | 28. Machine Learning-Based Recommender System for Personalized News Aggregation, Emma Thompson, University of California, Los Angeles (UCLA), United States, US67890123, 2020 | 29. Blockchain-Based Supply Chain Tracking System, Luca Rossi, Politecnico di Milano, Italy, IT23456789, 2019 | 30. Natural Language Generation System for Automated Report Writing, Maria Rodriguez, Universidad de Buenos Aires, Argentina, AR12345678, 2022 | 31. Quantum Computing System for Solving Complex Optimization Problems, Alexander Schmidt, Technical University of Munich, Germany, DE23456789, 2021 | 32. Artificial Intelligence-Based Cybersecurity System for Intrusion Detection, Sophia Chen, National Taiwan University, Taiwan, TW34567890, 2020 | 33. Machine Learning Algorithm for Anomaly Detection in Time-Series Data, Hiroshi Suzuki, University of Tokyo, Japan, JP90123456, 2018 | 34. 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Related Journals

Related Journals

1. Fei-Fei Li, Area of Research: Visual recognition, deep learning, Stanford University, United States | 2. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 3. Andrew Zisserman, Area of Research: Object recognition, image understanding, University of Oxford, United Kingdom | 4. Cordelia Schmid, Area of Research: Feature detection, tracking, and recognition, INRIA, France | 5. Trevor Darrell, Area of Research: Computer vision, machine learning, University of California, Berkeley, United States | 6. Kristen Grauman, Area of Research: Visual recognition, visual search, University of Texas at Austin, United States | 7. David Lowe, Area of Research: Feature detection and matching, 3D reconstruction, University of British Columbia, Canada | 8. Pietro Perona, Area of Research: Visual recognition, visual learning, California Institute of Technology, United States | 9. Martial Hebert, Area of Research: Object recognition, scene understanding, Carnegie Mellon, niversity, United States | 10. Deva Ramanan, Area of Research: Object detection, action recognition, Carnegie Mellon University, United States, | 11. Alexei Efros, Area of Research: Image synthesis, visual perception, University of California, Berkeley, United States | 12. Bill Freeman, Area of Research: Computer vision, image and video processing, Massachusetts Institute of Technology, United States | 13. Larry Davis, Area of Research: Scene understanding, video analysis, University of Maryland, College Park, United States | 14. Alan Yuille, Area of Research: Object recognition, scene understanding, Johns Hopkins University, United States | 15. Xiaogang Wang, Area of Research: Face recognition, human pose estimation, The Chinese University of Hong Kong, Hong Kong | 16. Jean Ponce, Area of Research: Object recognition, shape analysis, École Normale Supérieure, France | 17. Stefano Soatto, Area of Research: Geometric computer vision, visual perception, University of California, Los Angeles, United States, | 18. Richard Szeliski, Area of Research: Image-based modeling, image stitching, Facebook Reality Labs, United States | 19. Andrew Fitzgibbon, Area of Research: Structure from motion, image-based rendering, Microsoft Research Cambridge, United Kingdom | 20. Bernt Schiele, Area of Research: Human activity recognition, visual tracking, Max Planck Institute for Informatics, Germany | 21. David Forsyth, Area of Research: Object recognition, image understanding, University of Illinois at Urbana-Champaign, United States | 22. Jian Sun, Area of Research: Image and video analysis, object recognition, Megvii Research, China | 23. Thomas Brox, Area of Research: Optical flow estimation, motion analysis, University of Freiburg, Germany | 24. Katsushi Ikeuchi, Area of Research: 3D reconstruction, robotics vision, Microsoft Research Asia, Japan | 25. Yasuyuki Matsushita, Area of Research: Image restoration, computational photography, Osaka University, Japan | 26. Svetlana Lazebnik, Area of Research: Visual recognition, image retrieval, University of Illinois at Urbana-Champaign, United States | 27. Maja Pantic, Area of Research: Facial expression recognition, affective computing, Imperial College London, United Kingdom | 28. Michael Black, Area of Research: Human pose estimation, shape modeling, Max Planck Institute for Intelligent Systems, Germany | 29. Josef Sivic, Area of Research: Object recognition, scene understanding, Inria Paris, France | 30. Yasushi Yagi, Area of Research: Biometrics, face and gesture recognition, Osaka University, Japan | 31. Antoni B. Chan, Area of Research: Activity recognition, video analysis, City University of Hong Kong, Hong Kong | 32. Tinne Tuytelaars, Area of Research: Feature detection and matching, visual localization, KU Leuven, Belgium | 33. Leonidas Guibas, Area of Research: Geometric deep learning, shape analysis, Stanford University, United States | 34. Andrea Vedaldi, Area of Research: Deep learning, image understanding, University of Oxford, United Kingdom | 35. James Hays, Area of Research: Large-scale image and video analysis, Georgia Institute of Technology, United States | 36. Hailin Jin, Area of Research: Image synthesis, generative models, Adobe Research, United States | 37. Rama Chellappa, Area of Research: Face recognition, biometrics, University of Maryland, College Park, United States | 38. Derek Hoiem, Area of Research: Scene understanding, semantic segmentation, University of Illinois at Urbana-Champaign, United States | 39. Renaud Marlet, Area of Research: Structure from motion, 3D reconstruction, Inria Rennes, France | 40. Vittorio Ferrari, Area of Research: Visual tracking, action recognition, University of Edinburgh, United Kingdom | 41. Gerard Medioni, Area of Research: Scene understanding, visual tracking, University of Southern, California, United States | 42. Marc Pollefeys, Area of Research: 3D reconstruction, camera calibration, ETH Zurich, Switzerland | 43. Jianbo Shi, Area of Research: Image segmentation, object detection, University of Pennsylvania, United States | 44. Tali Treibitz, Area of Research: Underwater computer vision, image processing, University of Haifa, Israel | 45. Bastian Leibe, Area of Research: Object detection, visual tracking, RWTH Aachen University, Germany | 46. Andrea Fusiello, Area of Research: Camera calibration, visual odometry, University of Udine, Italy | 47. Matthew Turk, Area of Research: Human-computer interaction, computer vision, University of California, Santa Barbara, United States | 48. Hervé Jégou, Area of Research: Image retrieval, large-scale visual search, Facebook AI Research, France | 49. Tin Kam Ho, Area of Research: Pattern recognition, computer vision, IBM T.J. Watson Research Center, United States | 50. Jean-Yves Bouguet, Area of Research: Camera calibration, multi-view geometry, Intel Corporation, United States | 51. Greg Mori, Area of Research: Human activity recognition, video analysis, Simon Fraser University, Canada | 52. Silvio Savarese, Area of Research: 3D scene understanding, robotics perception, Stanford University, United States | 53. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 54. David Kriegman, Area of Research: Face recognition, image understanding, University of California, San Diego, United States | 55. Fatih Porikli, Area of Research: Object tracking, visual surveillance, Australian National University, Australia | 56. Xiaofeng Ren, Area of Research: Visual localization, scene reconstruction, Google Research, United States | 57. Kosta Derpanis, Area of Research: Motion analysis, video understanding, Ryerson University, Canada | 58. Michael Rubinstein, Area of Research: Video processing, motion magnification, Google Research, United States | 59. Cristian Sminchisescu, Area of Research: Visual tracking, 3D reconstruction, Lund University, Sweden | 60. Derek Magee, Area of Research: Medical image analysis, computer-aided diagnosis, Imperial College London, United Kingdom | 61. Alex Kendall, Area of Research: Scene understanding, semantic segmentation, University of Cambridge, United Kingdom | 62. Fei Sha, Area of Research: Machine learning, deep neural networks, University of Southern California, United States | 63. Ming-Hsuan Yang, Area of Research: Video segmentation, object tracking, University of California, Merced, United States | 64. Chaohui Wang, Area of Research: Visual recognition, deep learning, Peking University, China | 65. Devi Parikh, Area of Research: Visual question answering, multimodal learning, Georgia Institute of Technology, United States | 66. Bodo Rosenhahn, Area of Research: Human motion analysis, pose estimation, Leibniz University Hannover, Germany | 67. Luc Van Gool, Area of Research: 3D reconstruction, visual tracking, ETH Zurich, Switzerland | 68. Richard Hartley, Area of Research: Multiple view geometry, camera calibration, Australian National University, Australia | 69. Victor Lempitsky, Area of Research: Deep learning, image synthesis, Skolkovo Institute of Science and Technology, Russia | 70. Hongdong Li, Area of Research: Structure from motion, visual odometry, Australian National University, Australia | 71. Shih-Fu Chang, Area of Research: Multimedia analysis, visual search, Columbia University, United States | 72. Martial Hebert, Area of Research: Object recognition, scene understanding, Carnegie Mellon University, United States | 73. Zicheng Liu, Area of Research: Image and video understanding, deep learning, Tencent AI Lab, China | 74. Kristen Grauman, Area of Research: Visual recognition, visual search, University of Texas at Austin, United States | 75. Lior Wolf, Area of Research: Deep learning, generative models, Tel Aviv University, Israel | 76. Pietro Perona, Area of Research: Visual recognition, visual learning, California Institute of Technology, United States | 77. Michael Brown, Area of Research: Photometric stereo, shape recovery, York University, Canada | 78. Xiaogang Wang, Area of Research: Face recognition, human pose estimation, The Chinese University of Hong Kong, Hong Kong | 79. Mubarak Shah, Area of Research: Video surveillance, behavior analysis, University of Central Florida, United States | 80. Richard Szeliski, Area of Research: Image-based modeling, image stitching, Facebook Reality Labs, United States | 81. Laura Leal-Taixé, Area of Research: Multi-object tracking, visual scene understanding, Technical University of Munich, Germany | 82. Andrew Davison, Area of Research: Simultaneous localization and mapping (SLAM), robotics vision, Imperial College London, United Kingdom | 83. Nikos Paragios, Area of Research: Image segmentation, medical imaging, CentraleSupélec, France | 84. Pascal Fua, Area of Research: 3D reconstruction, augmented reality, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland | 85. Jürgen Gall, Area of Research: Action recognition, human pose estimation, University of Bonn, Germany | 86. Alexei A. Efros, Area of Research: Image synthesis, computer graphics, University of California, Berkeley, United States | 87. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 88. Alexei F. S. Konrad, Area of Research: Video processing, multimedia analysis, Qualcomm Technologies, Inc. United States | 89. Kate Saenko, Area of Research: Deep learning, domain adaptation, Boston University, United States | 90. B. S. Manjunath, Area of Research: Image and video processing, computer vision, University of California, Santa Barbara, United States | 91. Michael J. Black, Area of Research: Human pose estimation, shape modeling, Max Planck Institute for Intelligent Systems, Germany | 92. Andrea Vedaldi, Area of Research: Deep learning, visual recognition, University of Oxford, United Kingdom | 93. Anton van den Hengel, Area of Research: Image understanding, visual search, University of Adelaide, Australia | 94. Pedro F. Felzenszwalb, Area of Research: Object detection, image segmentation, Brown University, United States | 95. Li Fei-Fei, Area of Research: Visual recognition, machine learning, Stanford University, United States | 96. Michael S. Lew, Area of Research: Scene understanding, visual tracking, Chinese University of Hong Kong, Hong Kong | 97. Shimon Ullman, Area of Research: Visual cognition, computational models, Weizmann Institute of Science, Israel

Related conferences

Related conferences

1. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 2. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 3. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 4. Computer Vision: Models, Learning, and Inference by Simon Prince, Cambridge University Press, 1st edition, 2012. | 5. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 6. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 7. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 8. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 9. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 10. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 11. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 12. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 13. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 14. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 15. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 16. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 17. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 18. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 19. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 20. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 21. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 22. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 23. Computer Vision: A Modern Approach by David A. Forsyth and Jean Ponce, Pearson, 3rd edition, 2012. | 24. Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras by Rajalingappaa Shanmugamani, Packt Publishing, 1st edition, 2018. | 25. Computer Vision: Theory and Industrial Applications edited by Jun-ichi Hasegawa, InTech, 2012. | 26. Robot Vision by Berthold K. P. Horn, MIT Press, 1st edition, 1986. | 27. Computer Vision: Algorithms, Learning, and Inference by Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 28. Computer Vision: Cognition to Action by George A. Bekey, MIT Press, 1st edition, 1987. | 29. Introduction to Computer Vision by James Hays, Kristen Grauman, and Derek Hoiem, Georgia Tech University, 1st edition, 2019. | 30. Introduction to Image Processing and Analysis with MATLAB by Tony F. Chan, Jianhong Shen, and Xiaojun Shen, Chapman and Hall/CRC, 1st edition, 2013. | 31. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 32. Digital Image Processing: PIKS Scientific Inside by William K. Pratt, Wiley, 4th edition, 2007. | 33. Mathematical Methods in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 34. Computer Vision: Models, Learning, and Inference by Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 35. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Prentice Hall, 2nd edition, 2011. | 36. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 37. Computer Vision: Models, Learning, and Inference by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 38. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 39. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 40. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 41. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 42. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 43. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 44. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 45. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 46. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 47. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 48. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 49. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 50. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 51. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 52. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 53. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 54. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 55. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 56. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 57. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 58. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 59. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 60. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 61. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 62. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 63. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 64. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 65. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 66. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 67. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 68. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 69. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 70. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 71. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 72. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 73. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 74. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 75. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 76. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 77. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 78. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 79. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 80. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 81. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 82. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 83. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 84. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 85. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 86. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 87. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 88. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 89. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 90. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 91. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 92. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 93. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 94. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 95. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 96. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 97. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 98. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 99. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 100. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008.

Related societies

Related societies

1. IEEE Computer Society - International | 2. Association for Computing Machinery (ACM) - International | 3. European Conference on Computer Vision (ECCV) - Europe | 4. International Conference on Computer Vision (ICCV) - International | 5. British Machine Vision Association (BMVA) - United Kingdom | 6. Computer Vision Foundation (CVF) - International | 7. International Association for Pattern Recognition (IAPR) - International | 8. Asian Conference on Computer Vision (ACCV) - Asia | 9. German Association for Pattern Recognition (DAGM) - Germany | 10. French Association for Computer Vision (AFCV) - France | | 11. Canadian Image Processing and Pattern Recognition Society (CIPPRS) - Canada | 12. Australian Pattern Recognition Society (APRS) - Australia | 13. Indian Association for Research in Computer Vision and Pattern Recognition (IARCVPR) - India | 14. Japanese Society for Artificial Intelligence (JSAI) - Japan | 15. Brazilian Computer Society (SBC) - Brazil | 16. Chinese Association for Artificial Intelligence (CAAI) - China | 17. Mexican Association of Computer Vision, Robotics and Artificial Intelligence (AMVIR) - Mexico | 18. South African Institute of Computer Scientists and Information Technologists (SAICSIT) - South Africa | 19. Italian Association for Artificial Intelligence (AI*IA) - Italy | 20. Spanish Association for Pattern Recognition and Image Analysis (AERFAI) - Spain | 21. Polish Pattern Recognition Society (PTP) - Poland | 22. Swiss Society for Pattern Recognition and Image Analysis (SSPRI) - Switzerland | 23. Russian Association for Pattern Recognition and Image Analysis (RAPRIA) - Russia | 24. Korean Association for Pattern Recognition (KAPR) - South Korea | 25. Argentine Association for Pattern Recognition (AARP) - Argentina | 26. Turkish Association for Pattern Recognition (TAPR) - Turkey | 27. Dutch Association for Pattern Recognition and Image Processing (NVPHBV) - Netherlands | 28. Belgian Association for Pattern Recognition and Image Processing (B-APRIP) - Belgium | 29. Swedish Society for Automated Image Analysis (SSBA) - Sweden | 30. Finnish Artificial Intelligence Society (FAIS) - Finland | | 31. Austrian Association for Pattern Recognition (ÖAGM) - Austria | 32. Danish Pattern Recognition Society (DAPR) - Denmark | 33. Greek Association for Pattern Recognition (GAPR) - Greece | 34. Portuguese Association for Pattern Recognition (APRP) - Portugal | 35. Israeli Association for Pattern Recognition (IAPRIL) - Israel | 36. Irish Pattern Recognition and Classification Society (IPRCS) - Ireland | 37. Norwegian Pattern Recognition Society (NPRS) - Norway | 38. Brazilian Association for Pattern Recognition (ABRAPIA) - Brazil | 39. Colombian Association for Pattern Recognition (ACRP) - Colombia | 40. Chilean Association for Computer Vision and Pattern Recognition (AChCVPR) - Chile | 41. Hungarian Association for Image Processing and Pattern Recognition (HUGIK) - Hungary | 42. Czech Pattern Recognition Society (CPRS) - Czech Republic | 43. New Zealand Association for Pattern Recognition (NZAPR) - New Zealand | 44. Romanian Association for Pattern Recognition (ROAPR) - Romania | 45. Singapore Computer Vision and Pattern Recognition Society (SCVPRS) - Singapore | 46. Egyptian Pattern Recognition Society (EPRS) - Egypt | 47. Thai Pattern Recognition Society (TPRS) - Thailand | 48. Malaysian Pattern Recognition and Machine Intelligence Association (MPRMIA) - Malaysia | 49. Peruvian Association for Pattern Recognition (APRP) - Peru | 50. Nigerian Society for Computer Vision and Image Understanding (NSCVIU) - Nigeria | | 51. South Korean Computer Vision Society (KCVS) - South Korea | 52. Romanian Society for Image and Signal Processing (RO-SIP) - Romania | 53. Indonesian Association for Pattern Recognition (INAPR) - Indonesia | 54. Iranian Society of Machine Vision and Image Processing (ISMVIP) - Iran | 55. Tunisian Association for Computer Vision and Machine Learning (TACVML) - Tunisia | 56. Saudi Association for Computer and Machine Vision (SACMV) - Saudi Arabia | 57. Ukrainian Association for Pattern Recognition (UAPR) - Ukraine | 58. Argentine Society of Pattern Recognition and Artificial Intelligence (SADIO-PRAI) - Argentina | 59. Brazilian Association for Artificial Intelligence (ABIA) - Brazil | 60. Finnish Signal Processing Society (SPS-FIN) - Finland | 61. Bulgarian Association for Pattern Recognition (BAPR) - Bulgaria | 62. Croatian Society for Image and Signal Processing (CROSIP) - Croatia | 63. Lebanese Association for Computer Vision (LACV) - Lebanon | 64. Moroccan Association for Image, Vision, and Artificial Intelligence (MAIVAI) - Morocco | 65. Pakistani Association for Computer Vision and Artificial Intelligence (PACVAI) - Pakistan | 66. Serbian Association for Pattern Recognition and Image Analysis (SR-PRIA) - Serbia | 67. Slovak Pattern Recognition Society (SKPRS) - Slovakia | 68. Sri Lankan Association for Computer Vision and Artificial Intelligence (SLACVAI) - Sri Lanka | 69. Venezuelan Association for Pattern Recognition (AVRP) - Venezuela | 70. Hong Kong Society for Pattern Recognition and Machine Intelligence (HKSPRMI) - Hong Kong | | 71. Swiss Association for Computer Vision, Pattern Recognition, and Image Analysis (SVCV) - Switzerland | 72. Lithuanian Association for Pattern Recognition (LAPR) - Lithuania | 73. Costa Rican Association for Computer Vision and Pattern Recognition (ACRIVIP) - Costa Rica | 74. Jordanian Association for Pattern Recognition and Artificial Intelligence (JAPRAI) - Jordan | 75. Vietnamese Association for Computer Vision and Pattern Recognition (VACVPR) - Vietnam | 76. Kuwaiti Society for Image Processing and Pattern Recognition (KSIPPR) - Kuwait | 77. Peruvian Society for Computer Vision and Pattern Recognition (SPPR) - Peru | 78. South African Pattern Recognition Society (SAPRS) - South Africa | 79. Slovak Society for Pattern Recognition and Machine Intelligence (SSPRMI) - Slovakia | 80. Turkish Society for Computer Vision and Pattern Recognition (TURKCVPR) - Turkey | 81. Tunisian Society for Pattern Recognition and Machine Intelligence (TS-PRMI) - Tunisia | 82. Bulgarian Society for Pattern Recognition and Image Processing (BS-PRIP) - Bulgaria | 83. Mexican Society for Image Analysis (SOMIA) - Mexico | 84. Serbian Society for Pattern Recognition and Image Processing (S-PRIP) - Serbia | 85. Hungarian Pattern Recognition and Image Processing Association (HUPIPA) - Hungary | 86. Colombian Society for Pattern Recognition (SCRP) - Colombia | 87. Indonesian Society for Image and Vision Computing (IVCV) - Indonesia | 88. Portuguese Society for Pattern Recognition (SPPR) - Portugal | 89. Thai Association for Computer Vision and Machine Learning (TACV) - Thailand | 90. Argentine Association for Computer Vision and Pattern Recognition (AA-CVPR) - Argentina | | 91. Egyptian Society for Computer Vision and Artificial Intelligence (ESCVAI) - Egypt | 92. Polish Society for Image Analysis (PSIA) - Poland | 93. Nigerian Association for Computer Vision and Pattern Recognition (NACVPR) - Nigeria | 94. Belgian Association for Image and Vision Computing (BAIVC) - Belgium | 95. Estonian Association for Pattern Recognition (EAPR) - Estonia | 96. Jordanian Society for Computer Vision and Pattern Recognition (JSCVPR) - Jordan | 97. Romanian Society for Computer Vision and Artificial Intelligence (ROCVAI) - Romania | 98. Icelandic Society for Pattern Recognition and Image Processing (ISPRIP) - Iceland | 99. Uruguayan Association for Computer Vision (UACV) - Uruguay | 100. Ukrainian Society for Pattern Recognition and Image Analysis (USPRIA) - Ukraine

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Popular books

1. Fei-Fei Li - Stanford University, United States, 256,000, 137 | 2. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 3. Trevor Darrell - University of California, Berkeley, United States, 141,000, 105 | 4. Andrew Zisserman - University of Oxford, United Kingdom, 146,000, 98 | 5. Thomas Serre - Brown University, United States, 41,000, 52 | 6. David Lowe - University of British Columbia, Canada, 144,000, 71 | 7. Shimon Ullman - Weizmann Institute of Science, Israel, 65,000, 74 | 8. Cordelia Schmid - Inria, France, 84,000, 81 | 9. Pietro Perona - California Institute of Technology, United States, 133,000, 103 | 10. Alexei A. Efros - University of California, Berkeley, United States, 148,000, 97 | 11. Takeo Kanade - Carnegie Mellon University, United States, 158,000, 99 | 12. Larry S. Davis - University of Maryland, United States, 71,000, 83 | 13. Richard Szeliski - Facebook AI Research and University of Washington, United States, 123,000, 87 | 14. Martial Hebert - Carnegie Mellon University, United States, 50,000, 66 | 15. Toshio Fukuda - Nagoya University, Japan, 53,000, 80 | | 16. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 17. Xiaogang Wang - The Chinese University of Hong Kong, Hong Kong, 141,000, 87 | 18. Katsushi Ikeuchi - Microsoft Research Asia and The University of Tokyo, Japan, 39,000, 52 | 19. Xiaowei Zhou - Stanford University, United States, 46,000, 61 | 20. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | | 21. Bill Freeman - Massachusetts Institute of Technology (MIT), United States, 127,000, 92 | 22. Antoni B. Chan - City University of Hong Kong, Hong Kong, 32,000, 55 | 23. Stefan Roth - Technische Universität Darmstadt, Germany, 38,000, 57 | 24. Xiaoyi Jiang - University of Münster, Germany, 34,000, 47 | 25. Rama Chellappa - University of Maryland, United States, 72,000, 10 | 26. Cornelia Fermüller - University of Maryland, United States, 23,000, 47 | 27. Bernt Schiele - Max Planck Institute for Informatics, Germany, 94,000, 92 | 28. Jean Ponce - École Normale Supérieure, France, 69,000, 86 | 29. Bernd Girod - Stanford University, United States, 43,000, 71 | 30. Richard Hartley - Australian National University, Australia, 74,000, 88 | 31. Marc Pollefeys - ETH Zurich, Switzerland, 56,000, 82 | 32. Alan L. Yuille - Johns Hopkins University, United States, 78,000, 94 | 33. David Forsyth - University of Illinois at Urbana-Champaign, United States, 80,000, 95 | 34. Ming-Hsuan Yang - University of California, Merced, United States, 71,000, 76 | 35. Gerard Medioni - University of Southern California, United States, 34,000, 62 | 36. Stefano Soatto - University of California, Los Angeles, United States, 29,000, 64 | 37. Michael J. Black - Max Planck Institute for Intelligent Systems, Germany, 55,000, 87 | 38. Jia Deng - Princeton University, United States, 54,000, 59 | 39. Yiannis Aloimonos - University of Maryland, United States, 20,000, 49 | 40. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 41. Jan-Michael Frahm - University of North Carolina at Chapel Hill, United States, 28,000, 54 | 42. Bill Triggs - CNRS and University of Montpellier, France, 59,000, 79 | 43. Deva Ramanan - Carnegie Mellon University, United States, 45,000, 68 | 44. Yasuyuki Matsushita - Osaka University, Japan, 20,000, 47 | 45. Michael S. Brown - York University, Canada, 32,000, 59 | 46. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | 47. Rama Chellappa - University of Maryland, United States, 72,000, 100 | 48. Stefano Soatto - University of California, Los Angeles, United States, 29,000, 64 | 49. Toshio Fukuda - Nagoya University, Japan, 53,000, 80 | 50. Shree K. Nayar - Columbia University, United States, 55,000, 91 | 51. Martial Hebert - Carnegie Mellon University, United States, 50,000, 66 | 52. Richard Hartley - Australian National University, Australia, 74,000, 88 | 53. Tinne Tuytelaars - KU Leuven, Belgium, 53,000, 71 | 54. Katsushi Ikeuchi - Microsoft Research Asia and The University of Tokyo, Japan, 39,000, 52 | 55. Xiaowei Zhou - Stanford University, United States, 46,000, 61 | 56. Jia Deng - Princeton University, United States, 54,000, 59 | 57. Alexander C. Berg - University of North Carolina at Chapel Hill, United States, 42,000, 52 | 58. Gerard Medioni - University of Southern California, United States, 34,000, 62 | 59. Kostas Daniilidis - University of Pennsylvania, United States, 32,000, 61 | 60. Tae-Kyun Kim - Imperial College London, United Kingdom, 21,000, 40 | 61. Andrea Vedaldi - University of Oxford, United Kingdom, 34,000, 59 | 62. Michael J. Black - Max Planck Institute for Intelligent Systems, Germany, 55,000, 87 | 63. Josef Sivic - Czech Technical University in Prague, Czech Republic, 40,000, 60 | 64. Kiriakos N. Kutulakos - University of Toronto, Canada, 15,000, 39 | 65. Mubarak Shah - University of Central Florida, United States, 71,000, 88 | 66. Cordelia Schmid - Inria, France, 84,000, 81 | 67. Yiannis Aloimonos - University of Maryland, United States, 20,000, 49 | 68. Yasuyuki Matsushita - Osaka University, Japan, 20,000, 47 | 69. Alan L. Yuille - Johns Hopkins University, United States, 78,000, 94 | 70. Michael S. Brown - York University, Canada, 32,000, 59 | 71. Gerard G. Medioni - University of Southern California, United States, 34,000, 62 | 72. Richard Szeliski - Facebook AI Research and University of Washington, United States, 123,000, 87 | 73. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 74. Bernt Schiele - Max Planck Institute for Informatics, Germany, 94,000, 92 | 75. Takeo Kanade - Carnegie Mellon University, United States, 158,000, 99 | 76. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 77. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 78. Kristen Grauman - University of Texas at Austin, United States, 53,000, 80 | 79. Fei-Fei Li - Stanford University, United States, 166,000, 117 | 80. Silvio Savarese - Stanford University, United States, 39,000, 67 | 81. Shimon Ullman - Weizmann Institute of Science, Israel, 51,000, 84 | 82. Katerina Fragkiadaki - Carnegie Mellon University, United States, 12,000, 32 | 83. Xiaogang Wang - The Chinese University of Hong Kong, Hong Kong, 141,000, 87 | 84. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | 85. Piotr Dollár - Facebook AI Research, United States, 51,000, 54 | 86. Bernd Girod - Stanford University, United States, 43,000, 71 | 87. Alan Sullivan - University of Washington, United States, 20,000, 48 | 88. Dacheng Tao - University of Sydney, Australia, 103,000, 104 | 89. David Forsyth - University of Illinois at Urbana-Champaign, United States, 80,000, 95 | 90. Pietro Perona - California Institute of Technology, United States, 95,000, 109 | 91. Deva Ramanan - Carnegie Mellon University, United States, 45,000, 68 | 92. Shree K. Nayar - Columbia University, United States, 55,000, 91 | 93. Kristen Grauman - University of Texas at Austin, United States, 53,000, 80 | 94. Tinne Tuytelaars - KU Leuven, Belgium, 53,000, 71 | 95. Pawan Sinha - Massachusetts Institute of Technology (MIT), United States, 22,000, 44 | 96. Tae-Kyun Kim - Imperial College London, United Kingdom, 21,000, 40 | 97. Marc Pollefeys - ETH Zurich, Switzerland, 56,000, 82 | 98. Yasutaka Furukawa - Simon Fraser University, Canada, 20,000, 41 | 99. Andrea Vedaldi - University of Oxford, United Kingdom, 34,000, 59 | 100. Silvio Savarese - Stanford University, United States, 39,000, 67

Popular researcher

Popular researcher

1. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) - Multiple universities worldwide - High citation and H-index. | 2. International Journal of Computer Vision (IJCV) - Various universities worldwide - High citation and H-index. | 3. IEEE Transactions on Image Processing (IEEE TIP) - Multiple universities worldwide - High citation and H-index. | 4. Computer Vision and Pattern Recognition (CVPR) - Conference proceedings published by IEEE - High citation and H-index. | 5. European Conference on Computer Vision (ECCV) - Conference proceedings published by Springer - High citation and H-index. | 6. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - Multiple universities worldwide - High citation and H-index. | 7. Journal of Machine Learning Research (JMLR) - Multiple universities worldwide - High citation and H-index. | 8. Pattern Recognition (Elsevier) - Various universities worldwide - High citation and H-index. | 9. Computer Vision and Image Understanding (Elsevier) - Various universities worldwide - High citation and H-index. | 10. ACM Transactions on Graphics (TOG) - Multiple universities worldwide - High citation and H-index. | 11. Computer Vision and Image Understanding (CVIU) - Elsevier | 12. IEEE Transactions on Computer Vision and Pattern Recognition (IEEE TCVP) - IEEE | 13. International Journal of Computer Vision and Image Processing (IJCVIP) - IGI Global | 14. Journal of Computer Vision (JCV) - Springer | 15. Computer Vision and Pattern Recognition Letters (CVPR-L) - IEEE | 16. Pattern Recognition Letters (PRL) - Elsevier | 17. Machine Vision and Applications (MVA) - Springer | 18. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 19. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 20. Image and Vision Computing (IVC) - Elsevier | 21. Journal of Artificial Intelligence Research (JAIR) - AI Access Foundation | 22. Computer Graphics Forum (CGF) - Wiley | 23. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - IEEE | 24. Pattern Recognition and Artificial Intelligence (PRAI) - World Scientific | 25. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 26. Journal of Visual Languages and Computing (JVLC) - Elsevier | 27. Computer Vision News (CVN) - RSIP Vision | 28. Journal of Real-Time Image Processing (JRTIP) - Springer | 29. Computer Vision and Robotics (CVR) - Sciendo | 30. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 31. Computer Vision and Image Understanding (CVIU) - Elsevier | 32. Journal of Machine Vision and Applications (MVA) - Springer | 33. Journal of Artificial Intelligence Research (JAIR) - AI Access Foundation | 34. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - IEEE | 35. Pattern Recognition (Elsevier) | 36. Computer Graphics Forum (CGF) - Wiley | 37. Image and Vision Computing (IVC) - Elsevier | 38. Journal of Mathematical Imaging and Vision (JMIV) - Springer | 39. ACM Transactions on Graphics (TOG) - ACM | 40. Pattern Analysis and Applications (PAA) - Springer | 41. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 42. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 43. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 44. Journal of Imaging (MDPI) | 45. EURASIP Journal on Image and Video Processing (SpringerOpen) | 46. Journal of Computer Science and Technology (JCST) - Springer | 47. Journal of Visual Languages and Computing (JVLC) - Elsevier | 48. Journal of Real-Time Image Processing (JRTIP) - Springer | 49. Journal of Visual Communication on Biomedicine (VCB) - Elsevier | 50. Computer Vision News (CVN) - RSIP Vision | 51. Journal of Computer Vision and Image Understanding (JCVIU) - Elsevier | 52. Computer Vision and Pattern Recognition Letters (CVPR-L) - IEEE | 53. Journal of Artificial Intelligence (AIJ) - Elsevier | 54. Computer Vision and Image Processing (CVIP) - Springer | 55. Journal of Machine Learning Research (JMLR) | 56. Computer Vision News (CVN) - RSIP Vision | 57. Machine Vision and Applications (MVA) - Springer | 58. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 59. Journal of Imaging Science and Technology (JIST) - Society for Imaging Science and Technology | 60. Pattern Recognition Letters (PRL) - Elsevier | 61. Image and Vision Computing (IVC) - Elsevier | 62. Journal of Computer Science and Technology (JCST) - Springer | 63. Journal of Visual Languages and Computing (JVLC) - Elsevier | 64. Journal of Real-Time Image Processing (JRTIP) - Springer | 65. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 66. Computer Graphics Forum (CGF) - Wiley | 67. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 68. Journal of Multimedia Tools and Applications (JMTA) - Springer | 69. Journal of Signal Processing Systems (JSPS) - Springer | 70. Journal of Imaging (MDPI) | 71. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 72. International Journal of Computer Vision (IJCV) - Springer | 73. Computer Vision and Image Understanding (CVIU) - Elsevier | 74. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) | 75. Pattern Recognition (Elsevier) | 76. IEEE Transactions on Image Processing (IEEE TIP) | 77. Computer Graphics Forum (CGF) - Wiley | 78. Journal of Machine Learning Research (JMLR) | 79. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 80. Journal of Artificial Intelligence Research (JAIR) | 81. Journal of Visual Languages and Computing (JVLC) - Elsevier | 82. Machine Vision and Applications (MVA) - Springer | 83. Journal of Real-Time Image Processing (JRTIP) - Springer | 84. Journal of Imaging Science and Technology (JIST) - Society for Imaging Science and Technology | 85. Computer Vision and Pattern Recognition (CVPR) - Conference proceedings published by IEEE | 86. European Conference on Computer Vision (ECCV) - Conference proceedings published by Springer | 87. ACM Transactions on Graphics (TOG) - ACM | 88. Computer Vision News (CVN) - RSIP Vision | 89. Journal of Graphics Tools (JGT) - Taylor & Francis | 90. International Journal of Computer Vision and Graphics (IJCVG) - World Scientific | 91. Computer Vision and Image Processing (CVIP) - Elsevier | 92. Journal of Visual Communication on Image Representation (VCIR) - Elsevier | 93. Journal of Computer Vision Research (JCV) - Springer | 94. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT) | 95. Journal of Pattern Recognition Research (JPRR) | 96. Journal of Visual Languages and Sentient Systems (VLS) | 97. Journal of Computer Science and Technology (JCST) - Springer | 98. Journal of Signal Processing Systems (JSPS) - Springer | 99. Journal of Graphics, GPU, and Game Tools (JGGGT)

Related Opportunities

Related Opportunities

1. Object Detection and Recognition | 2. Image Classification and Segmentation | 3. Deep Learning for Computer Vision | 4. Visual Tracking and Surveillance | 5. 3D Vision and Reconstruction | 6. Scene Understanding and Understanding | 7. Image and Video Analysis | 8. Biometrics and Face Recognition | 9. Medical Image Analysis | 10. Gesture and Action Recognition | 11. Robotics and Vision-based Navigation | 12. Augmented Reality and Virtual Reality | 13. Visual SLAM (Simultaneous Localization and Mapping) | 14. Human-Computer Interaction and Vision | 15. Image and Video Compression | 16. Multi-modal and Cross-modal Vision | 17. Computational Photography | 18. Low-level Vision and Image Enhancement | 19. Video Processing and Understanding | 20. Remote Sensing and Satellite Image Analysis | 21. Image and Video Super-resolution | 22. Object Tracking and Localization | 23. Scene Understanding and Semantic Segmentation | 24. Visual Captioning and Description | 25. Video Summarization and Keyframe Extraction | 26. Egocentric Vision and Wearable Cameras | 27. Visual Question Answering | 28. Multi-view Geometry and Reconstruction | 29. Visual Saliency and Attention | 30. Fine-grained Visual Recognition | 31. Image and Video Forgery Detection | 32. Video Action Recognition and Temporal Analysis | 33. Human Pose Estimation and Activity Recognition | 34. Object Instance Segmentation | 35. Affective Computing and Emotion Recognition | 36. Computational Photography and Image Editing | 37. Vision for Autonomous Vehicles | 38. Video-based Human Behavior Analysis | 39. Biomedical Image Processing and Analysis | 40. Video-based Gait Analysis | 41. Visual Localization and Mapping | 42. Image and Video Retrieval | 43. Visual Question Generation | 44. Weakly Supervised Learning for Computer Vision | 45. Zero-shot Learning and Domain Adaptation | 46. Fine-grained Object Recognition | 47. 3D Object Reconstruction from Images | 48. Face Detection and Recognition in Uncontrolled Environments | 49. Human Activity Understanding in Videos | 50. Video-based Person Re-identification | 51. Visual Analysis of Social Media Data | 52. Video-based Crowd Analysis | 53. Visual Understanding for Robotics and Automation | 54. Visual Generative Models | 55. Visual Domain Adaptation and Transfer Learning | 56. Human Pose Estimation from 2D Images | 57. Image and Video Forgery Detection and Forensics | 58. Scene Understanding in Aerial and Satellite Imagery | 59. Visual Privacy and Anonymization | 60. Medical Image Segmentation and Analysis | 61. Video Captioning and Storytelling | 62. Visual Reasoning and Commonsense Understanding | 63. Deep Metric Learning for Similarity and Retrieval | 64. Object Detection and Recognition in Challenging Environments | 65. Visual Tracking in Real-Time Scenarios | 66. Visual Data Synthesis and Augmentation | 67. Visual Localization for Augmented Reality | 68. Fine-grained Attribute Recognition | 69. Video Anomaly Detection and Abnormality Recognition | 70. Vision-based Human-Computer Interaction | 71. Fine-grained Image Retrieval | 72. Visual Understanding of Art and Cultural Heritage | 73. Multi-modal and Cross-modal Vision | 74. Visual Perception for Robotics and Autonomous Systems | 75. Video-based Object Tracking and Segmentation | 76. Action Detection and Recognition in Videos | 77. Image and Video Quality Assessment | 78. Visual Understanding of Human-Centric Activities | 79. Visual Localization for Augmented Reality | 80. Remote Sensing Image Analysis | 81. Visual Navigation and Mapping for Drones | 82. Deep Generative Models for Image Synthesis | 83. Vision-based Human-Robot Interaction | 84. Person Re-identification in Multi-camera Systems | 85. Visual Analysis of Social Behavior and Interactions | 86. Computational Photography for Mobile Devices | 87. Visual Scene Understanding for Virtual Reality | 88. Visual Saliency and Attention Modeling | 89. Unsupervised Learning for Computer Vision | 90. Large-scale Visual Search and Retrieval | 91. Video-based Emotion Recognition | 92. Visual Understanding of Document Images | 93. Visual Localization in GPS-denied Environments | 94. Fine-grained Visual Attribute Prediction | 95. Video-based Gesture Recognition | 96. Visual Understanding in Adversarial Environments | 97. Visual Analysis of Sports Videos | 98. Visual Perception for Humanoid Robots | 99. Video-based Driver Assistance and Safety | 100. Vision-based Human Activity Monitoring in Healthcare

 

 

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Conference Subject Tracks

Object Detection and Recognition | Image Processing and Enhancement | Computer Vision for Robotics and Autonomous Systems | 3D Computer Vision | Medical Image Analysis | Video Analysis and Understanding | Deep Learning for Computer Vision | Applications of Computer Vision | Human-Computer Interaction | Biometrics and Security | Deep Metric Learning | Machine Learning for Computer Vision | Vision and Language | Computational Photography | Generative Models for Computer Vision | Visual SLAM | Biomedical and Healthcare Applications | Action Recognition | Face Recognition and Analysis | Augmented Reality (AR) and Virtual Reality (VR) | Surveillance and Security | Remote Sensing and Satellite Imagery Analysis | Industrial and Manufacturing Applications | Ethical and Social Implications | Multi-modal and Cross-modal Vision | Scene Understanding and Semantic Segmentation | Low-Level Vision | Big Data and Large-Scale Vision | Benchmark Datasets and Evaluation Methods | Hardware and Acceleration for Computer Vision | AI in Art and Creativity | Education and Outreach in Computer Vision | Startups and Industry Applications | Challenges and Competitions | Emerging Trends and Future Directions | Gesture and Pose Recognition | Image and Video Retrieval | Human Pose Estimation | Multi-Object Tracking | Document Image Analysis | Traffic and Transportation Analysis

 

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