Fetching the paper…
Reading the bibliography…
In this paper, we introduce FairFaceGAN, a fairness-aware facial Image-to-Image translation model, mitigating the problem of unwanted translation in protected attributes (e.g., gender, age, race) during facial attributes editing.
Controlling biases and diversity in diverse image-to-image translation
Yaxing Wang, Abel Gonzalez-Garcia, Joost van de Weijer, and Luis Herranz · 1907
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
Earlier work this paper cites.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
Earlier work this paper cites.
Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
Earlier work this paper cites.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
Earlier work this paper cites.
Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
Earlier work this paper cites.
Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi · 2017
Earlier work this paper cites.
Age progression/regression by conditional adversarial autoencoder
Zhifei Zhang, Yang Song, and Hairong Qi · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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
Cited alongside, same era.
Demystifying mmd gans
Mikołaj Bińkowski, Dougal J Sutherland, Michael Arbel, and Arthur Gretton · 2018
Cited alongside, same era.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Learning fixed points in generative adversarial networks: From image-to-image translation to disease detection and localization
Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B Gotway, Yoshua Bengio, and Jianming Liang · 2019
Later among the works it cites.
Joint multi-view texture super-resolution and intrinsic decomposition
Vagia Tsiminaki, Wei Dong, Martin R. Oswald, and Marc Pollefeys · 2019
Later among the works it cites.
Predictive inequity in object detection
Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern · 2019
Later among the works it cites.
Base-detail image inpainting
Ruonan Zhang, Yurui Ren, Jingfei Qiu, and Ge Li · 2019
Later among the works it cites.
Residual multiscale based single image deraining
Yupei Zheng, Xin Yu, Miaomiao Liu, and Shunli Zhang · 2019
Later among the works it cites.
Disentangling latent space for vae by label relevant/irrelevant dimensions
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
Cited alongside, same era.
Age and gender bias in pedestrian detection algorithms
Martim Brandao · 2019
Cited alongside, same era.
Flexibly fair representation learning by disentanglement
Elliot Creager, David Madras, Jorn Jacobsen, Marissa Weis, Kevin Jordan Swersky, Toniann Pitassi, and Richard Zemel · 2019
Cited alongside, same era.
Does object recognition work for everyone?
Terrance de Vries, Ishan Misra, Changhan Wang, and Laurens van der Maaten · 2019
Cited alongside, same era.
Learning not to learn: Training deep neural networks with biased data
Byungju Kim, Hyunwoo Kim, Kyungsu Kim, Sungjin Kim, and Junmo Kim · 2019
Cited alongside, same era.
Where are the masks: Instance segmentation with image-level supervision
Issam H Laradji, David Vazquez, and Mark Schmidt · 2019
Cited alongside, same era.
Discovering fair representations in the data domain
Novi Quadrianto, Viktoriia Sharmanska, and Oliver Thomas · 2019
Cited alongside, same era.
Zhilin Zheng and Li Sun · 2019
Later among the works it cites.
Is there a trade-off between fairness and accuracy? a perspective using mismatched hypothesis testing
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, and Kush R Varshney · 2020
Closest in time.
Garbage in, garbage out? do machine learning application papers in social computing report where human-labeled training data comes from?
R Stuart Geiger, Kevin Yu, Yanlai Yang, Mindy Dai, Jie Qiu, Rebekah Tang, and Jenny Huang · 2020
Closest in time.
Unsupervised image-to-image translation via fair representation of gender bias
Sunhee Hwang and Hyeran Byun · 2020
Closest in time.
Pulse: Self-supervised photo upsampling via latent space exploration of generative models
Sachit Menon, Alexandru Damian, Shijia Hu, Nikhil Ravi, and Cynthia Rudin · 2020
Closest in time.
Readme: Representation learning by fairness-aware disentangling method
Sungho Park, Dohyung Kim, Sunhee Hwang, and Hyeran Byun · 2020
Closest in time.
Bounding the fairness and accuracy of classifiers from population statistics
Sivan Sabato and Elad Yom-Tov · 2020
Closest in time.
What a machine learning tool that turns obama white can (and can’t) tell us about ai bias, 2020
James Vincent · 2020
Closest in time.