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It is expensive to collect training data for every possible domain that a vision model may encounter when deployed.
Contrastive examples for addressing the tyranny of the majority
Viktoriia Sharmanska, Lisa Anne Hendricks, Trevor Darrell, and Novi Quadrianto · 2004
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Rewriting a deep generative model
David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, and Antonio Torralba · 2007
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The caltech-ucsd birds-200-2011 dataset, 2011
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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The mnist database of handwritten digit images for machine learning research
Li Deng · 2012
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
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Simultaneous deep transfer across domains and tasks
Eric Tzeng, Judy Hoffman, Trevor Darrell, and Kate Saenko · 2015
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Few-shot adversarial domain adaptation, 2017
Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh, and Gianfranco Doretto · 2017
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Maximum classifier discrepancy for unsupervised domain adaptation
Kuniaki Saito, Kohei Watanabe, Yoshitaka Ushiku, and Tatsuya Harada · 2017
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Deep hashing network for unsupervised domain adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan · 2017
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Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Women also snowboard: Overcoming bias in captioning models
Lisa Anne Hendricks, Kaylee Burns, Kate Saenko, Trevor Darrell, and Anna Rohrbach · 2018
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Learning not to learn: Training deep neural networks with biased data
Byungju Kim, Hyunwoo Kim, Kyungsu Kim, Sungjin Kim, and Junmo Kim · 2018
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Tell me where to look: Guided attention inference network
Kunpeng Li, Ziyan Wu, Kuan-Chuan Peng, Jan Ernst, and Yun Fu · 2018
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Generate to adapt: Aligning domains using generative adversarial networks
Swami Sankaranarayanan, Yogesh Balaji, Carlos Domingo Castillo, and Rama Chellappa · 2018
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Why can’t i dance in the mall? learning to mitigate scene bias in action recognition
Jinwoo Choi, Chen Gao, C. E. Joseph Messou, and Jia-Bin Huang · 2019
Cited alongside, same era.
Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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Do ImageNet classifiers generalize to ImageNet?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar · 2019
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Distributionally robust neural networks
Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 2019
Cited alongside, same era.
Interpretations are useful: Penalizing explanations to align neural networks with prior knowledge
Openclip, July 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Wilds: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, et al · 2021
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Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, A. Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Laura Rieger, Chandan Singh, William Murdoch, and Bin Yu · 2020
Cited alongside, same era.
Class-imbalanced domain adaptation: an empirical odyssey
Shuhan Tan, Xingchao Peng, and Kate Saenko · 2020
Cited alongside, same era.
Adversarial learning for zero-shot domain adaptation
Jinghua Wang and Jianmin Jiang · 2020
Cited alongside, same era.
Progressive adversarial networks for fine-grained domain adaptation
Sinan Wang, Xinyang Chen, Yunbo Wang, Mingsheng Long, and Jianmin Wang · 2020
Cited alongside, same era.
Invariant risk minimization
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Stylegan-nada: Clip-guided domain adaptation of image generators
Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, and Daniel Cohen-Or · 2021
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Editing a classifier by rewriting its prediction rules
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, and Aleksander Madry · 2021
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Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Mike Li, Jong Wook Kim, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, and Ludwig Schmidt · 2021
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Source-free unsupervised domain adaptation with surrogate data generation
Hao Yan, Yuhong Guo, and Chunsheng Yang · 2021
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Multi-source few-shot domain adaptation
Xiangyu Yue, Zangwei Zheng, Hari Prasanna Das, Kurt Keutzer, and Alberto Sangiovanni Vincentelli · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan · 2022
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Vqgan-clip: Open domain image generation and editing with natural language guidance
Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff · 2022
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Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, and Percy Liang · 2022
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On guiding visual attention with language specification
Suzanne Petryk, Lisa Dunlap, Keyan Nasseri, Joseph Gonzalez, Trevor Darrell, and Anna Rohrbach · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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