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Recently, vision transformer (ViT) and its variants have achieved promising performances in various computer vision tasks.
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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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Recognizing indoor scenes
Ariadna Quattoni and Antonio Torralba · 2009
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The pascal visual object classes (VOC) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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The Caltech-UCSD Birds-200-2011 Dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Cats and dogs
Omkar M. Parkhi, Andrea Vedaldi, Andrew Zisserman, and C. V. Jawahar · 2012
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3d object representations for fine-grained categorization
Krause Jonathan, Stark Michael, Deng Jia, and Li Fei-Fei · 2013
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Fine-grained visual classification of aircraft
S. Maji, J. Kannala, E. Rahtu, M. Blaschko, and A. Vedaldi · 2013
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Describing textures in the wild
M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, , and A. Vedaldi · 2014
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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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Deep networks with stochastic depth
Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, and Kilian Q Weinberger · 2016
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Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Channel pruning for accelerating very deep neural networks
Yihui He, Xiangyu Zhang, and Jian Sun · 2017
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Pruning filters for efficient convnets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Thinet: A filter level pruning method for deep neural network compression
Jian-Hao Luo, Jianxin Wu, and Weiyao Lin · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
Cited alongside, same era.
The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
Cited alongside, same era.
Mixup: Beyond Empirical Risk Minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz · 2018
Cited alongside, same era.
Reducing transformer depth on demand with structured dropout
Angela Fan, Edouard Grave, and Armand Joulin · 2019
Cited alongside, same era.
Star-Transformer
Qipeng Guo, Xipeng Qiu, Pengfei Liu, Yunfan Shao, Xiangyang Xue, and Zheng Zhang · 2019
Cited alongside, same era.
Rethinking attention with Performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, and Adrian Weller · 2021
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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, Jakob Uszkoreit, and Neil Houlsby · 2021
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Efficient vision transformers via fine-grained manifold distillation
Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, and Dacheng Tao · 2021
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All tokens matter: Token labeling for training better vision transformers
Zihang Jiang, Qibin Hou, Li Yuan, Daquan Zhou, Yujun Shi, Xiaojie Jin, Anran Wang, and Jiashi Feng · 2021
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Swin Transformer: Hierarchical vision transformer using shifted windows
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Filter pruning via geometric median for deep convolutional neural networks acceleration
Yang He, Ping Liu, Ziwei Wang, Zhilan Hu, and Yi Yang · 2019
Cited alongside, same era.
Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
Cited alongside, same era.
Losing heads in the lottery: Pruning transformer attention in neural machine translation
Maximiliana Behnke and Kenneth Heafield · 2020
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
RandAugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
Cited alongside, same era.
Transformers are rnns: Fast autoregressive transformers with linear attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and François Fleuret · 2020
Cited alongside, same era.
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Closest in time.
Token pooling in vision transformers
Dmitrii Marin, Jen-Hao Rick Chang, Anurag Ranjan, Anish Prabhu, Mohammad Rastegari, and Oncel Tuzel · 2021
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Patch slimming for efficient vision transformers
Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, and Dacheng Tao · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Herve Jegou · 2021
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PVTv2: Improved baselines with pyramid vision transformer
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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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
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End-to-end video instance segmentation with transformers
Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen, Baoshan Cheng, Hao Shen, and Huaxia Xia · 2021
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Evo-ViT: Slow-Fast token evolution for dynamic vision transformer
Yifan Xu, Zhijie Zhang, Mengdan Zhang, Kekai Sheng, Ke Li, Weiming Dong, Liqing Zhang, Changsheng Xu, and Xing Sun · 2021
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NViT: Vision transformer compression and parameter redistribution
Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, and Jan Kautz · 2021
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Tokens-to-Token ViT: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zi-Hang Jiang, Francis E.H. Tay, Jiashi Feng, and Shuicheng Yan · 2021
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Mingjian Zhu, Kai Han, Yehui Tang, and Yunhe Wang · 2021
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