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Recently, Vision Transformers (ViT), with the self-attention (SA) as the de facto ingredients, have demonstrated great potential in the computer vision community.
Discrete cosine transform
Nasir Ahmed, T_ Natarajan, and Kamisetty R Rao · 1974
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The jpeg still picture compression standard
Gregory K Wallace · 1992
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Cited alongside, same era.
Unified perceptual parsing for scene understanding
Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, and Jian Sun · 2018
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Drop an octave: Reducing spatial redundancy in convolutional neural networks with octave convolution
Yunpeng Chen, Haoqi Fan, Bing Xu, Zhicheng Yan, Yannis Kalantidis, Marcus Rohrbach, Shuicheng Yan, and Jiashi Feng · 2019
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Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Reppoints: Point set representation for object detection
Local-to-global self-attention in vision transformers
Jinpeng Li, Yichao Yan, Shengcai Liao, Xiaokang Yang, and Ling Shao · 2021
Closest in time.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, and Peter W Battaglia · 2021
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Conformer: Local features coupling global representations for visual recognition
Zhiliang Peng, Wei Huang, Shanzhi Gu, Lingxi Xie, Yaowei Wang, Jianbin Jiao, and Qixiang Ye · 2021
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Dynamicvit: Efficient vision transformers with dynamic token sparsification
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Ze Yang, Shaohui Liu, Han Hu, Liwei Wang, and Stephen Lin · 2019
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Big transfer (bit): General visual representation learning
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, and Neil Houlsby · 2020
Cited alongside, same era.
Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár · 2020
Cited alongside, same era.
A review of interactions between peripheral and foveal vision
Emma EM Stewart, Matteo Valsecchi, and Alexander C Schütz · 2020
Cited alongside, same era.
Score-cam: Score-weighted visual explanations for convolutional neural networks
Haofan Wang, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel, and Xia Hu · 2020
Cited alongside, same era.
Learning in the frequency domain
Kai Xu, Minghai Qin, Fei Sun, Yuhao Wang, Yen-Kuang Chen, and Fengbo Ren · 2020
Cited alongside, same era.
Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, and Cho-Jui Hsieh · 2021
Closest in time.
Sparse r-cnn: End-to-end object detection with learnable proposals
Peize Sun, Rufeng Zhang, Yi Jiang, Tao Kong, Chenfeng Xu, Wei Zhan, Masayoshi Tomizuka, Lei Li, Zehuan Yuan, Changhu Wang, et al · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Going deeper with image transformers
Hugo Touvron, Matthieu Cord, Alexandre Sablayrolles, Gabriel Synnaeve, and Hervé Jégou · 2021
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Scaling local self-attention for parameter efficient visual backbones
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake Hechtman, and Jonathon Shlens · 2021
Closest in time.
Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
Closest in time.
Cvt: Introducing convolutions to vision transformers
Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang · 2021
Closest in time.
Early convolutions help transformers see better
Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollár, and Ross Girshick · 2021
Closest in time.
Focal self-attention for local-global interactions in vision transformers
Jianwei Yang, Chunyuan Li, Pengchuan Zhang, Xiyang Dai, Bin Xiao, Lu Yuan, and Jianfeng Gao · 2021
Closest in time.
Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zihang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
Closest in time.
Multi-scale vision longformer: A new vision transformer for high-resolution image encoding
Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, and Jianfeng Gao · 2021
Closest in time.
Aggregating nested transformers
Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, and Tomas Pfister · 2021
Closest in time.