Los Alamitos, California \u2013 01 July 2022<\/strong> \u2013 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), the largest gathering of professionals from across the world and from every aspect of the computer vision, machine learning (ML), and artificial intelligence (AI) industries, successfully concluded this week, breaking records with over 10,250 conference registrants and 2000 technical papers presented.<\/p>\n Computer vision is a field of AI that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs \u2014 and take actions or make recommendations based on that information. CVPR 2022 convened the brightest minds in the field for a week-long program of papers, keynotes, workshops, tutorials, posters, virtual learning, and discussion, and showcased the advancement of computer vision on a global scale.<\/p>\n CVPR\u2019s annual conference covered an extensive range of computer vision, AI, and ML topics and applications; the top five research categories at CVPR 2022 ranked by the number of papers accepted this year are:<\/p>\n CVPR 2022 experienced a record number of paper submissions \u2013 8,161 \u2013 of which only 2,064 were accepted at the conference.<\/p>\n CVPR annually recognizes such research through its best papers awards, and the event is internationally known for its prestigious awards program. From this year\u2019s 33 finalists selected from the 2,064 accepted papers, the Awards Committee presented the following awards:<\/p>\n Best Paper Award Best Paper Honorable Mention Best Student Paper Award Best Student Paper Honorable Mention\u00ad\u00ad The event\u2019s exhibit hall packed with 137 exhibitors provided an abundance of advancements to explore and included companies noted for their AI programs such as Apple, Meta, Microsoft, and TikTok, as well as autonomous driving companies like Argo AI, Tesla, cruise, and Zoox.<\/p>\n Exhibitor highlights include:<\/p>\n The CVPR 2022 keynote speaker lineup included the following\u00a0high-profile industry leaders:<\/p>\n A panel session covering \u201cEmbodied Computer Vision,\u201d featured Martial Hebert, Carnegie Mellon University, as the moderator, with panelists that included Kristen Grauman, University of Texas, Austin, and Meta AI; Nicholas Roy, Zoox, and MIT; and Michael Ryoo, Stonybrook University and Google.<\/p>\n The 2023 CVPR event will take place in Vancouver, from June 17 to 23, 2023.<\/p>\n \u00a0<\/p>\n About CVPR\u00a0<\/strong><\/p>\n The Computer Vision and Pattern Recognition Conference (CVPR)\u00a0 is the premier annual computer vision and pattern recognition conference. With first-in-class technical content, the main program, tutorials, workshops, a leading-edge expo, and attended by more than 7,500 people annually, CVPR creates a one-of-a-kind opportunity for networking, recruiting, inspiration, and motivation.<\/p>\n About the IEEE Computer Society<\/strong><\/p>\n The IEEE Computer Society is the world\u2019s home for computer science, engineering, and technology. A global leader in providing access to computer science research, analysis, and information, the IEEE Computer Society offers a comprehensive array of unmatched products, services, and opportunities for individuals at all stages of their professional careers. Known as the premier organization that empowers the people who drive technology, the IEEE Computer Society offers international conferences, peer-reviewed publications, a unique digital library, and training programs.<\/p>\n About the Computer Vision Foundation<\/strong><\/p>\n The Computer Vision Foundation is a non-profit organization whose purpose is to foster and support research on all aspects of computer vision. Together with the IEEE Computer Society, it co-sponsors the two largest computer vision conferences: CVPR and the International Conference on Computer Vision (ICCV).<\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n \u00a0<\/span><\/p>\n<\/p><\/div>\n![\"\"](\"https:\/\/ieeecs-media.computer.org\/wp-media\/2022\/07\/01202025\/CVPR-exhibits-image-300x200.jpg\")
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<\/strong>Learning to Solve Hard Minimal Problems
Authors: Petr Hruby, Timothy Duff, Anton Leykin, and Tomas Pajdla<\/p>\n
<\/strong>Dual-Shutter Optical Vibration Sensing
Authors: Mark Sheinin, Dorian Chan, Matthew O\u2019Toole, Srinivasa Narasimhan<\/p>\n
<\/strong>EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
Authors: Hansheng Chen, Pichao Wang, Fan Wang, Wei Tian, Lu Xiong, Hao Li<\/p>\n
<\/strong>Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
Authors: Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan Barron, Pratul Srinivasan<\/p>\n\n
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