Vision Transformers
Vision Transformer is a deep learning model that adapts the transformer architecture, originally designed for natural language processing, to image classification by treating image patches as sequential tokens and leveraging self-attention mechanisms to capture global spatial dependencies.
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov et al. · arXiv (Cornell University) · 2020 · 21.6K citations · Full text
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu et al. · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 7.1K citations
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Tsinghua University
Beijing, China
36 h-index
109 publications
48.2K citations

Chinese Academy of Sciences
Beijing, China
33 h-index
139 publications
13.4K citations
University of Chinese Academy of Sciences
Beijing, China
31 h-index
101 publications
13K citations
Google (United States)
Mountain View, United States
28 h-index
131 publications
235.7K citations

Zhejiang University
Hangzhou, China
24 h-index
81 publications
7.5K citations
National University of Singapore
Singapore, Singapore
22 h-index
50 publications
25.2K citations
University of Science and Technology of China
Hefei, China
21 h-index
55 publications
37.8K citations

The University of Sydney
Sydney, Australia
21 h-index
55 publications
9.2K citations
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