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We propose GAN-Supervised Learning, a framework for learning discriminative models and their GAN-generated training data jointly end-to-end.
An iterative image registration technique with an application to stereo vision
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Antonio Torralba · 2001
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Transformation-invariant clustering using the EM algorithm
Brendan J. Frey and Nebojsa Jojic · 2003
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Lucas-kanade 20 years on: A unifying framework
Simon Baker and Iain Matthews · 2004
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k-means++: The advantages of careful seeding
David Arthur and Sergei Vassilvitskii · 2006
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Data driven image models through continuous joint alignment
Erik G. Learned-Miller · 2006
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Unsupervised joint alignment of complex images
G. B. Huang, V. Jain, and E. Learned-Miller · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Object instance sharing by enhanced bounding box correspondence
Santosh Divvala, Alexei Efros, and Martial Hebert · 2012
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Collection flow
Ira Kemelmacher-Shlizerman and Steven M Seitz · 2012
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Unsupervised joint alignment and clustering using bayesian nonparametrics
Marwan A. Mattar, Allen R. Hanson, and Erik G. Learned-Miller · 2012
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RASL: robust alignment by sparse and low-rank decomposition for linearly correlated images
YiGang Peng, Arvind Ganesh, John Wright, Wenli Xu, and Yi Ma · 2012
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2d human pose estimation: New benchmark and state of the art analysis
Mykhaylo Andriluka, Leonid Pishchulin, Peter Gehler, and Bernt Schiele · 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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A compositional model for low-dimensional image set representation
Hossein Mobahi, Ce Liu, and William T. Freeman · 2014
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
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Averageexplorer: Interactive exploration and alignment of visual data collections
Jun-Yan Zhu, Yong Jae Lee, and Alexei A Efros · 2014
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Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
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Adam: A method for stochastic optimization
Diederik 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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Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
Grant Van Horn, Steve Branson, Ryan Farrell, Scott Haber, Jessie Barry, Panos Ipeirotis, Pietro Perona, and Serge Belongie · 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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Flowweb: Joint image set alignment by weaving consistent, pixel-wise correspondences
Tinghui Zhou, Yong Jae Lee, Stella Yu, and Alexei A Efros · 2015
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Deepwarp: Photorealistic image resynthesis for gaze manipulation
Yaroslav Ganin, Daniil Kononenko, Diana Sungatullina, and Victor Lempitsky · 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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Dynamic filter networks
Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Warpnet: Weakly supervised matching for single-view reconstruction
Angjoo Kanazawa, David W Jacobs, and Manmohan Chandraker · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
Cited alongside, same era.
Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, and Honglak Lee · 2016
Cited alongside, same era.
View synthesis by appearance flow
Tinghui Zhou, Shubham Tulsiani, Weilun Sun, Jitendra Malik, and Alexei A Efros · 2016
Cited alongside, same era.
Generative visual manipulation on the natural image manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A. Efros · 2016
Cited alongside, same era.
Neural photo editing with introspective adversarial networks
Andrew Brock, Theodore Lim, James M Ritchie, and Nick Weston · 2017
Cited alongside, same era.
Fabio Henrique Kiyoiti dos Santos Tanaka and Claus Aranha · 2019
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This dataset does not exist: training models from generated images
Victor Besnier, Himalaya Jain, Andrei Bursuc, Matthieu Cord, and Patrick Pérez · 2020
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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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Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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Instance selection for gans
Terrance DeVries, Michal Drozdzal, and Graham W Taylor · 2020
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Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
Cited alongside, same era.
Adversarial feature learning
Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 2017
Cited alongside, same era.
Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martin Arjovsky, Olivier Mastropietro, and Aaron Courville · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Flownet 2.0: Evolution of optical flow estimation with deep networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
Inverse compositional spatial transformer networks
Chen-Hsuan Lin and Simon Lucey · 2017
Cited alongside, same era.
Transformation-grounded image generation network for novel 3d view synthesis
Eunbyung Park, Jimei Yang, Ersin Yumer, Duygu Ceylan, and Alexander C Berg · 2017
Cited alongside, same era.
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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Transforming and projecting images to class-conditional generative networks
Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, and Aaron Hertzmann · 2020
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Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 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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Articulation-aware canonical surface mapping
Nilesh Kulkarni, Abhinav Gupta, David F Fouhey, and Shubham Tulsiani · 2020
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Semantic correspondence as an optimal transport problem
Yanbin Liu, Linchao Zhu, Makoto Yamada, and Yi Yang · 2020
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Learning to compose hypercolumns for visual correspondence
Juhong Min, Jongmin Lee, Jean Ponce, and Minsu Cho · 2020
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Freeze the discriminator: a simple baseline for fine-tuning gans
Sangwoo Mo, Minsu Cho, and Jinwoo Shin · 2020
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Deep transformation-invariant clustering
Tom Monnier, Thibault Groueix, and Mathieu Aubry · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Implicit mesh reconstruction from unannotated image collections
Shubham Tulsiani, Nilesh Kulkarni, and Abhinav Gupta · 2020
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Andrey Voynov, Stanislav Morozov, and Artem Babenko · 2020
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Image gans meet differentiable rendering for inverse graphics and interpretable 3d neural rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, and Sanja Fidler · 2020
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Restyle: A residual-based stylegan encoder via iterative refinement
Yuval Alaluf, Or Patashnik, and Daniel Cohen-Or · 2021
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Learning to see by looking at noise
Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, and Antonio Torralba · 2021
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Ensembling with deep generative views
Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, and Richard Zhang · 2021
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Cats: Cost aggregation transformers for visual correspondence
Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, and Seungryong Kim · 2021
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GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds
Zekun Hao, Arun Mallya, Serge Belongie, and Ming-Yu Liu · 2021
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Generative models as a data source for multiview representation learning
Ali Jahanian, Xavier Puig, Yonglong Tian, and Phillip Isola · 2021
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Generative interventions for causal learning
Chengzhi Mao, Augustine Cha, Amogh Gupta, Hao Wang, Junfeng Yang, and Carl Vondrick · 2021
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Finding an unsupervised image segmenter in each of your deep generative models
Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, and Andrea Vedaldi · 2021
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Convolutional hough matching networks
Juhong Min and Minsu Cho · 2021
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Do 2d gans know 3d shape? unsupervised 3d shape reconstruction from 2d image gans
Xingang Pan, Bo Dai, Ziwei Liu, Chen Change Loy, and Ping Luo · 2021
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Lifting 2d stylegan for 3d-aware face generation
Yichun Shi, Divyansh Aggarwal, and Anil K Jain · 2021
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A good image generator is what you need for high-resolution video synthesis
Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris N. Metaxas, and Sergey Tulyakov · 2021
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Repurposing gans for one-shot semantic part segmentation
Nontawat Tritrong, Pitchaporn Rewatbowornwong, and Supasorn Suwajanakorn · 2021
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Datasetgan: Efficient labeled data factory with minimal human effort
Yuxuan Zhang, Huan Ling, Jun Gao, Kangxue Yin, Jean-Francois Lafleche, Adela Barriuso, Antonio Torralba, and Sanja Fidler · 2021
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