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In this paper, we show that popular Generative Adversarial Networks (GANs) exacerbate biases along the axes of gender and skin tone when given a skewed distribution of face-shots.
Fun with snapchat’s gender swapping filter
Eric Jang · 1970
Earlier work this paper cites.
Document Image Analysis , volume 39
Lawrence O’Gorman and Rangachar Kasturi · 1995
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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Can your face reveal how long you’ll live? New technology may provide the answer
Tara Bahrampour · 2014
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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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DCGAN implementation in Tensorflow
carpedm20 · 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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Machine Bias
Julia Angwin and Jeff Larson · 2016
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Data and algorithmic bias in the web
Ricardo Baeza-Yates · 2016
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NIPS 2016 tutorial: Generative Adversarial Networks
Ian Goodfellow · 2016
Earlier work this paper cites.
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
Earlier work this paper cites.
Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Earlier work this paper cites.
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, and Yi Zhang · 2017
Earlier work this paper cites.
Mode Regularized Generative Adversarial Networks
Tong Che, Yanran Li, Athul Paul Jacob, Yoshua Bengio, and Wenjie Li · 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.
CycleGAN
junyanz · 2017
Cited alongside, same era.
Unrolled Generative Adversarial Networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2017
Cited alongside, same era.
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U Gutmann, and Charles Sutton · 2017
Cited alongside, same era.
AdaGAN: Boosting Generative Models
Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, and Bernhard Schölkopf · 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.
Do GANs learn the distribution? Some Theory and Empirics
Sanjeev Arora, Andrej Risteski, and Yi Zhang · 2018
Cited alongside, same era.
Deep learning with synthetic data will democratize the tech industry
Evan Nisselson · 2018
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Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah Goodman, and Stefano Ermon · 2018
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https://www.reddit.com/r/MachineLearning/comments/bo4 orw/d_is_the_new_snapchat_gender_filter_ganbased/, 2019
r/MachineLearning - [D] Is the new Snapchat gender filter GAN-based? · 2019
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Biomedical image augmentation using Augmentor
Marcus D Bloice, Peter M Roth, and Andreas Holzinger · 2019
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The Deepfake Detection Challenge (DFDC) Preview Dataset, 2019
Brian Dolhansky, Russ Howes, Ben Pflaum, Nicole Baram, and Cristian Canton Ferrer · 2019
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Oxford Handbook on AI Ethics Book Chapter on Race and Gender
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Paulina Grnarova, Kfir Y Levy, Aurelien Lucchi, Nathanael Perraudin, Thomas Hofmann, and Andreas Krause · 2018
Cited alongside, same era.
Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size
Yuta Hiasa, Yoshito Otake, Masaki Takao, Takumi Matsuoka, Kazuma Takashima, Aaron Carass, Jerry L. Prince, Nobuhiko Sugano, and Yoshinobu Sato · 2018
Cited alongside, same era.
AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation
Sheng-Wei Huang, Che-Tsung Lin, Shu-Ping Chen, Yen-Yi Wu, Po-Hao Hsu, and Shang-Hong Lai · 2018
Cited alongside, same era.
CycleGAN and pix2pix in PyTorch
junyanz · 2018
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.
Evaluation of Mode Collapse in Generative Adversarial Networks
Sayeri Lala, Maha Shady, Anastasiya Belyaeva, and Molei Liu · 2018
Cited alongside, same era.
Timnit Gebru · 2019
Later among the works it cites.
Oregon became a testing ground for Amazon’s facial-recognition policing. But what if Rekognition gets it wrong?
Drew Harwell · 2019
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AI used for first time in job interviews in UK to find best applicants
Charles Hymas · 2019
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A New York school district is bringing in facial recognition software. Rights groups say it could spell trouble for students
Harmeet Kaur and Tony Marco · 2019
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The dark implications of facial swap filter technology
Paper Magazine · 2019
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Data Augmentation using Generative Adversarial Networks (CycleGAN) to Improve Generalizability in CT Segmentation Tasks
Veit Sandfort, Ke Yan, Perry J Pickhardt, and Ronald M Summers · 2019
Later among the works it cites.
Synthetic Data Is A Tool For Improving Training And Accuracy Of Deep Learning Systems
David A. Teich · 2019
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Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 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.
Gender Swap and CycleGAN in TensorFlow 2.0 – Ethan Yanjia Li, 2020
Ethan Yanjia Li · 2020
Closest in time.