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Recently, transformer architecture has demonstrated its significance in both Natural Language Processing (NLP) and Computer Vision (CV) 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, Geoffrey Hinton, et al · 2009
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Xiaodong Song · 2017
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
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Trojaning attack on neural networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 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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Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks
Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, and Vineeth N. Balasubramanian · 2018
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Sentinet: Detecting physical attacks against deep learning systems
Edward Chou, Florian Tramèr, Giancarlo Pellegrino, and Dan Boneh · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Scaling neural machine translation
Myle Ott, Sergey Edunov, David Grangier, and Michael Auli · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Cited alongside, same era.
Abs: Scanning neural networks for back-doors by artificial brain stimulation
Yingqi Liu, Wen-Chuan Lee, Guanhong Tao, Shiqing Ma, Yousra Aafer, and X. Zhang · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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How to fine-tune bert for text classification?
Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang · 2019
Cited alongside, same era.
Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, and Ben Y Zhao · 2019
Cited alongside, same era.
Xlnet: Generalized autoregressive pretraining for language understanding
Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Later among the works it cites.
Reveal of vision transformers robustness against adversarial attacks
Ahmed Aldahdooh, Wassim Hamidouche, and Olivier Déforges · 2021
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Tfe: A transformer architecture for occlusion aware facial expression recognition
Jixun Gao and Yuanyuan Zhao · 2021
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Adversarial token attacks on vision transformers
Ameya Joshi, Gauri Jagatap, and Chinmay Hegde · 2021
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Model Zoo
Jing Yu Koh · 2021
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Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le · 2019
Cited alongside, same era.
Cross-modal self-attention network for referring image segmentation
Linwei Ye, Mrigank Rochan, Zhi Liu, and Yang Wang · 2019
Cited alongside, same era.
Quantifying attention flow in transformers
Samira Abnar and Willem Zuidema · 2020
Cited alongside, same era.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 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.
Februus: Input purification defense against trojan attacks on deep neural network systems
Bao Gia Doan, Ehsan Abbasnejad, and Damith C Ranasinghe · 2020
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.
Monocular BEV Perception with Transformers in Autonomous Driving
Patrick Langechuan Liu · 2021
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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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On the robustness of vision transformers to adversarial examples
Kaleel Mahmood, Rigel Mahmood, and Marten van Dijk · 2021
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Towards robust vision transformer
Xiaofeng Mao, Gege Qi, Yuefeng Chen, Xiaodan Li, Ranjie Duan, Shaokai Ye, Yuan He, and Hui Xue · 2021
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On improving adversarial transferability of vision transformers
Muzammal Naseer, Kanchana Ranasinghe, Salman Hameed Khan, Fahad Shahbaz Khan, and Fatih Murat Porikli · 2021
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Tesla AI Day 2021 Review — Part 1: The Promise of Fully Self-Driving Cars
Alberto Romero · 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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Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer · 2021
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Face transformer for recognition
Yaoyao Zhong and Weihong Deng · 2021
Closest in time.