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Training deep networks with limited labeled data while achieving a strong generalization ability is key in the quest to reduce human annotation efforts.
Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules
Junji Shiraishi, Shigehiko Katsuragawa, Junpei Ikezoe, Tsuneo Matsumoto, Takeshi Kobayashi, Ken-ichi Komatsu, Mitate Matsui, Hiroshi Fujita, Yoshie Kodera, and Kunio Doi · 2000
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On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes
Andrew Y. Ng and Michael I. Jordan · 2001
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Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2004
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To recognize shapes, first learn to generate images
Geoffrey E. Hinton · 2007
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On deep generative models with applications to recognition
M. Ranzato, J. Susskind, V. Mnih, and G. Hinton · 2011
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Multimodal learning with deep boltzmann machines
Nitish Srivastava and Russ R Salakhutdinov · 2012
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Automatic segmentation of skin lesions from dermatological photographs
Jeffrey Luc Glaister · 2013
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Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee · 2013
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Ph 2-a dermoscopic image database for research and benchmarking
Teresa Mendonça, Pedro M Ferreira, Jorge S Marques, André RS Marcal, and Jorge Rozeira · 2013
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Two public chest x-ray datasets for computer-aided screening of pulmonary diseases
Stefan Jaeger, Sema Candemir, Sameer Antani, Yì-Xiáng J Wáng, Pu-Xuan Lu, and George Thoma · 2014
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Semi-supervised learning with deep generative models
Diederik P. Kingma, Danilo J. Rezende, Shakir Mohamed, and Max Welling · 2014
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A. Efros · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 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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Semantic segmentation using adversarial networks
Pauline Luc, Camille Couprie, Soumith Chintala, and Jakob Verbeek · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Semi-supervised learning with generative adversarial networks
Augustus Odena · 2016
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Invertible conditional gans for image editing
Guim Perarnau, Joost van de Weijer, Bogdan Raducanu, and Jose M. Álvarez · 2016
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Regularization with stochastic transformations and perturbations for deep semi-supervised learning
Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen · 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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Generative visual manipulation on the natural image manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A Efros · 2016
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Semi-supervised learning for network-based cardiac mr image segmentation
Wenjia Bai, Ozan Oktay, Matthew Sinclair, Hideaki Suzuki, Martin Rajchl, Giacomo Tarroni, Ben Glocker, Andrew King, Paul M Matthews, and Daniel Rueckert · 2017
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Neural photo editing with introspective adversarial networks
Andrew Brock, Theodore Lim, James M. Ritchie, and Nick Weston · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, and Aaron C. Courville · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Precise recovery of latent vectors from generative adversarial networks
Zachary C. Lipton and Subarna Tripathi · 2017
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Semi supervised semantic segmentation using generative adversarial network
N. Souly, C. Spampinato, and M. Shah · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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Semantic image inpainting with deep generative models
R. A. Yeh, C. Chen, T. Y. Lim, A. G. Schwing, M. Hasegawa-Johnson, and M. N. Do · 2017
Cited alongside, same era.
Gan dissection: Visualizing and understanding generative adversarial networks
David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B Tenenbaum, William T Freeman, and Antonio Torralba · 2018
Cited alongside, same era.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2018
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
Cited alongside, same era.
Weakly-supervised semantic segmentation network with deep seeded region growing
Z. Huang, X. Wang, J. Wang, W. Liu, and J. Wang · 2018
Cited alongside, same era.
Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Editing in style: Uncovering the local semantics of gans
Edo Collins, Raja Bala, Bob Price, and Sabine Süsstrunk · 2020
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Meta-sim2: Unsupervised learning of scene structure for synthetic data generation
Jeevan Devaranjan, Amlan Kar, and Sanja Fidler · 2020
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Semi-supervised semantic segmentation needs strong, varied perturbations
Geoffrey French, Samuli Laine, Timo Aila, Michal Mackiewicz, and Graham Finlayson · 2020
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Milking cowmask for semi-supervised image classification
Geoff French, Avital Oliver, and Tim Salimans · 2020
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Adversarial learning for semi-supervised semantic segmentation
Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang · 2018
Cited alongside, same era.
nnu-net: Self-adapting framework for u-net-based medical image segmentation
Fabian Isensee, Jens Petersen, Andre Klein, David Zimmerer, Paul F. Jaeger, Simon Kohl, Jakob Wasserthal, Gregor Koehler, Tobias Norajitra, Sebastian Wirkert, and Klaus H. Maier-Hein · 2018
Cited alongside, same era.
Few-shot 3d multi-modal medical image segmentation using generative adversarial learning
Arnab Kumar Mondal, Jose Dolz, and Christian Desrosiers · 2018
Cited alongside, same era.
Chest x-ray analysis of tuberculosis by deep learning with segmentation and augmentation
Sergii Stirenko, Yuriy Kochura, Oleg Alienin, Oleksandr Rokovyi, Yuri Gordienko, Peng Gang, and Wei Zeng · 2018
Cited alongside, same era.
High-resolution image synthesis and semantic manipulation with conditional gans
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, and Bryan Catanzaro · 2018
Cited alongside, same era.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 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.
Your classifier is secretly an energy based model and you should treat it like one
Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen, David Duvenaud, Mohammad Norouzi, and Kevin Swersky · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, and Michal Valko · 2020
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Image processing using multi-code gan prior
Jinjin Gu, Yujun Shen, and Bolei Zhou · 2020
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Data-efficient image recognition with contrastive predictive coding
Olivier J. Henaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, and Aaron van den Oord · 2020
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Neural networks with recurrent generative feedback
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, and Anima Anandkumar · 2020
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Transforming and projecting images into 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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CHAOS Challenge - Combined (CT-MR) Healthy Abdominal Organ Segmentation
A. Emre Kavur, N. Sinem Gezer, Mustafa Barış, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savaş Özkan, Bora Baydar, Dmitry Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Sinem Aslan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, and M. Alper Selver · 2020
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Guided collaborative training for pixel-wise semi-supervised learning
Zhanghan Ke, Di Qiu, Kaican Li, Qiong Yan, and Rynson W. H. Lau · 2020
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Federated simulation for medical imaging
Daiqing Li, Amlan Kar, Nishant Ravikumar, Alejandro F. Frangi, and Sanja Fidler · 2020
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Transformation-consistent self-ensembling model for semisupervised medical image segmentation
Xiaomeng Li, Lequan Yu, Hao Chen, Chi-Wing Fu, Lei Xing, and Pheng-Ann Heng · 2020
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Variational amodal object completion for interactive scene editing
Huan Ling, David Acuna, Karsten Kreis, Seung Kim, and Sanja Fidler · 2020
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Hybrid discriminative-generative training via contrastive learning
Hao Liu and Pieter Abbeel · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Classmix: Segmentation-based data augmentation for semi-supervised learning
Viktor Olsson, Wilhelm Tranheden, Juliano Pinto, and Lennart Svensson · 2020
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Swapping autoencoder for deep image manipulation
Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, and Richard Zhang · 2020
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Hieu Pham, Qizhe Xie, Zihang Dai, and Quoc V. Le · 2020
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Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Jonah Philion and Sanja Fidler · 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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Encoding in style: a stylegan encoder for image-to-image translation
Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, and Daniel Cohen-Or · 2020
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A patient-centric dataset of images and metadata for identifying melanomas using clinical context
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein, Liam Caffery, Emmanouil Chousakos, Noel Codella, Marc Combalia, Stephen Dusza, Pascale Guitera, David Gutman, Allan Halpern, Harald Kittler, Kivanc Kose, Steve Langer, Konstantinos Lioprys, Josep Malvehy, Shenara Musthaq, Jabpani Nanda, Ofer Reiter, George Shih, Alexander Stratigos, Philipp Tschandl, Jochen Weber, and H. Peter Soyer · 2020
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Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, and Colin Raffel · 2020
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Stylegan2 distillation for feed-forward image manipulation
Yuri Viazovetskyi, Vladimir Ivashkin, and Evgeny Kashin · 2020
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Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, and Quoc V. Le · 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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In-domain gan inversion for real image editing
Jiapeng Zhu, Yujun Shen, Deli Zhao, and Bolei Zhou · 2020
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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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