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Fairness in visual recognition is becoming a prominent and critical topic of discussion as recognition systems are deployed at scale in the real world.
The foundations of cost-sensitive learning
Charles Elkan · 2001
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Discriminative learning under covariate shift
Steffen Bickel, Michael Brückner, and Tobias Scheffer · 2009
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Building classifiers with independency constraints
Toon Calders, Faisal Kamiran, and Mykola Pechenizkiy · 2009
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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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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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Improved techniques for training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Improved training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Low-shot visual recognition by shrinking and hallucinating features
Bharath Hariharan and Ross Girshick · 2017
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Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi · 2017
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2017
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Turning a blind eye: Explicit removal of biases and variation from deep neural network embeddings
Mohsan Alvi, Andrew Zisserman, and Christoffer Nellåker · 2018
Cited alongside, same era.
AI Fairness 360: An extensible toolkit for detecting, understanding, and mitigating unwanted algorithmic bias, Oct. 2018
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, and Yunfeng Zhang · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
Cited alongside, same era.
StarGAN: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
Cited alongside, same era.
Women also snowboard: Overcoming bias in captioning models
Lisa Anne Hendricks, Kaylee Burns, Kate Saenko, Trevor Darrell, and Anna Rohrbach · 2018
Rényi fair inference
Sina Baharlouei, Maher Nouiehed, Ahmad Beirami, and Meisam Razaviyayn · 2020
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Towards causal benchmarking of bias in face analysis algorithms
Guha Balakrishnan, Yuanjun Xiong, Wei Xia, and Pietro Perona · 2020
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Towards threshold invariant fair classification
Mingliang Chen and Min Wu · 2020
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Fair generative modeling via weak supervision
Kristy Choi, Aditya Grover, Rui Shu, and Stefano Ermon · 2020
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Google Cloud AI removes gender labels from Cloud Vision API to avoid bias, 02 2020
Khari Johnson · 2020
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Diverse image generation via self-conditioned GANs
Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, and Antonio Torralba · 2020
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Cited alongside, same era.
Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
Cited alongside, same era.
InclusiveFaceNet: Improving face attribute detection with race and gender diversity
Hee Jung Ryu, Hartwig Adam, and Margaret Mitchell · 2018
Cited alongside, same era.
FairGAN: Fairness-aware generative adversarial networks
Depeng Xu, Shuhan Yuan, Lu Zhang, and Xintao Wu · 2018
Cited alongside, same era.
Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
Cited alongside, same era.
Emotion classification with data augmentation using generative adversarial networks
Xinyue Zhu, Yifan Liu, Jiahong Li, Tao Wan, and Zengchang Qin · 2018
Cited alongside, same era.
Image2StyleGAN: How to embed images into the StyleGAN latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
Cited alongside, same era.
Seeing what a GAN cannot generate
David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, and Antonio Torralba · 2019
Cited alongside, same era.
FairALM: Augmented lagrangian method for training fair models with little regret
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, and Vikas Singh · 2020
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Learning from failure: Training debiased classifier from biased classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn, Jaeho Lee, and Jinwoo Shin · 2020
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Contrastive examples for addressing the tyranny of the majority, 2020
Viktoriia Sharmanska, Lisa Anne Hendricks, Trevor Darrell, and Novi Quadrianto · 2020
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Interpreting the latent space of GANs for semantic face editing
Yujun Shen, Jinjin Gu, Xiaoou Tang, and Bolei Zhou · 2020
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REVISE: A tool for measuring and mitigating bias in visual datasets
Angelina Wang, Arvind Narayanan, and Olga Russakovsky · 2020
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Towards fairness in visual recognition: Effective strategies for bias mitigation
Zeyu Wang, Klint Qinami, Ioannis Karakozis, Kyle Genova, Prem Nair, Kenji Hata, and Olga Russakovsky · 2020
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Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy
Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2020
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In-domain GAN inversion for real image editing
Jiapeng Zhu, Yujun Shen, Deli Zhao, and Bolei Zhou · 2020
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Directional bias amplification
Angelina Wang and Olga Russakovsky · 2021
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