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Recent research has shown that it is possible to find interpretable directions in the latent spaces of pre-trained Generative Adversarial Networks (GANs).
Principal component analysis
Svante Wold, Kim Esbensen, and Paul Geladi · 1987
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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What is a support vector machine?
William S Noble · 2006
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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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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 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, Alexander C. Berg, and Li Fei-Fei · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn · 2016
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High-resolution image synthesis and semantic manipulation with conditional gans, 2017
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, and Bryan Catanzaro · 2017
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Stackgan++: Realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N. Metaxas · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros · 2017
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2018
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Deepfakes: a new threat to face recognition? assessment and detection
Pavel Korshunov and Sébastien Marcel · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Ganalyze: Toward visual definitions of cognitive image properties
Lore Goetschalckx, Alex Andonian, Aude Oliva, and Phillip Isola · 2019
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On the” steerability” of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2019
Face identity disentanglement via latent space mapping
Yotam Nitzan, Amit Bermano, Yangyan Li, and Daniel Cohen-Or · 2020
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Controlling generative models with continuous factors of variations
Antoine Plumerault, Hervé Le Borgne, and Céline Hudelot · 2020
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Lightface: A hybrid deep face recognition framework
Sefik Ilkin Serengil and Alper Ozpinar · 2020
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Interfacegan: Interpreting the disentangled face representation learned by gans
Yujun Shen, Ceyuan Yang, Xiaoou Tang, and Bolei Zhou · 2020
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Closed-form factorization of latent semantics in gans
Yujun Shen and Bolei Zhou · 2020
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Single image deraining: A comprehensive benchmark analysis, 2019
Siyuan Li, Iago Breno Araujo, Wenqi Ren, Zhangyang Wang, Eric K. Tokuda, Roberto Hirata Junior, Roberto Cesar-Junior, Jiawan Zhang, Xiaojie Guo, and Xiaochun Cao · 2019
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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Spatial attentive single-image deraining with a high quality real rain dataset, 2019
Tianyu Wang, Xin Yang, Ke Xu, Shaozhe Chen, Qiang Zhang, and Rynson Lau · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Ganspace: Discovering interpretable gan controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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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
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On disentangled representations extracted from pretrained gans
Valentin Khrulkov, Leyla Mirvakhabova, Ivan Oseledets, and Artem Babenko · 2020
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Gan” steerability” without optimization
Nurit Spingarn-Eliezer, Ron Banner, and Tomer Michaeli · 2020
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Learned image downscaling for upscaling using content adaptive resampler
Wanjie Sun and Zhenzhong Chen · 2020
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Unsupervised discovery of interpretable directions in the gan latent space
Andrey Voynov and Artem Babenko · 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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Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows
Rameen Abdal, Peihao Zhu, Niloy J Mitra, and Peter Wonka · 2021
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Navigating the gan parameter space for semantic image editing
Anton Cherepkov, Andrey Voynov, and Artem Babenko · 2021
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Do generative models know disentanglement? contrastive learning is all you need
Xuanchi Ren, Tao Yang, Yuwang Wang, and Wenjun Zeng · 2021
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Designing an encoder for stylegan image manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, and Daniel Cohen-Or · 2021
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