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Transformers with powerful global relation modeling abilities have been introduced to fundamental computer vision tasks recently.
The dynamic representation of scenes
Ronald A Rensink · 2000
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Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 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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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, Alex Graves, and Koray Kavukcuoglu · 2014
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Multiple object recognition with visual attention
Jimmy Ba, Volodymyr Mnih, and Koray Kavukcuoglu · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 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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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz 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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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Boosting up scene text detectors with guided cnn
Xiaoyu Yue, Zhanghui Kuang, Zhaoyang Zhang, Zhenfang Chen, Pan He, Yu Qiao, and Wei Zhang · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
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Attention augmented convolutional networks
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, and Quoc V Le · 2019
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Bert: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Saccader: improving accuracy of hard attention models for vision
Gamaleldin F Elsayed, Simon Kornblith, and Quoc V Le · 2019
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Generative pretraining from pixels
Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, and Ilya Sutskever · 2020
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Uniter: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu · 2020
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Randaugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
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Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár · 2020
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Rethinking transformer-based set prediction for object detection
Zhiqing Sun, Shengcao Cao, Yiming Yang, and Kris Kitani · 2020
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Training data-efficient image transformers & distillation through attention
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Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, and Tim Salimans · 2019
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Local relation networks for image recognition
Han Hu, Zheng Zhang, Zhenda Xie, and Stephen Lin · 2019
Cited alongside, same era.
Visualbert: A simple and performant baseline for vision and language
Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, and Kai-Wei Chang · 2019
Cited alongside, same era.
Knowledge enhanced contextual word representations
Matthew E Peters, Mark Neumann, Robert L Logan IV, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A Smith · 2019
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Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, and Jonathon Shlens · 2019
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Nrtr: A no-recurrence sequence-to-sequence model for scene text recognition
Fenfen Sheng, Zhineng Chen, and Bo Xu · 2019
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Videobert: A joint model for video and language representation learning
Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, and Cordelia Schmid · 2019
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Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2020
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Axial-deeplab: Stand-alone axial-attention for panoptic segmentation
Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2020
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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 · 2020
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Scaling Autoregressive Video Models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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Visual transformers: Token-based image representation and processing for computer vision
Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Masayoshi Tomizuka, Kurt Keutzer, and Peter Vajda · 2020
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Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, and Baining Guo · 2020
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Robustscanner: Dynamically enhancing positional clues for robust text recognition
Xiaoyu Yue, Zhanghui Kuang, Chenhao Lin, Hongbin Sun, and Wayne Zhang · 2020
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End-to-end object detection with adaptive clustering transformer
Minghang Zheng, Peng Gao, Xiaogang Wang, Hongsheng Li, and Hao Dong · 2020
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
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Up-detr: Unsupervised pre-training for object detection with transformers
Zhigang Dai, Bolun Cai, Yugeng Lin, and Junying Chen · 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, et al · 2021
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
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