{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/global-context-vision-transformers","title":"Global Context Vision Transformers","arxiv_id":"2206.09959","date":"2022-06-20","proceeding":null,"authors":["Ali Hatamizadeh","Hongxu Yin","Greg Heinrich","Jan Kautz","Pavlo Molchanov"],"abstract":"We propose global context vision transformer (GC ViT), a novel architecture that enhances parameter and compute utilization for computer vision. 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