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Despite their recent successes, GAN models for semantic image synthesis still suffer from poor image quality when trained with only adversarial supervision.
A comparative study of texture measures with classification based on featured distributions
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Dual attention gans for semantic image synthesis
Hao Tang, Song Bai, and Nicu Sebe · 2002
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Edge guided gans with semantic preserving for semantic image synthesis
Hao Tang, Xiaojuan Qi, Dan Xu, Philip HS Torr, and Nicu Sebe · 2003
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Semantic image segmentation with deep convolutional nets and fully connected crfs
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Texture synthesis using convolutional neural networks
Leon Gatys, Alexander S Ecker, and Matthias Bethge · 2015
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Diederik P. Kingma and Jimmy Ba · 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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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2016
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Super-resolution with deep convolutional sufficient statistics
Joan Bruna, Pablo Sprechmann, and Yann LeCun · 2016
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Image style transfer using convolutional neural networks
L. A. Gatys, A. S. Ecker, and M. Bethge · 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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Generative adversarial text to image synthesis
Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Photographic image synthesis with cascaded refinement networks
Qifeng Chen and Vladlen Koltun · 2017
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Improved training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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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
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Semi supervised semantic segmentation using generative adversarial network
Nasim Souly, Concetto Spampinato, and Mubarak Shah · 2017
Unified perceptual parsing for scene understanding
Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, and Jian Sun · 2018
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The unusual effectiveness of averaging in gan training
Yasin Yaz, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar, et al · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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Diverse image synthesis from semantic layouts via conditional imle
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Dilated residual networks
Fisher Yu, Vladlen Koltun, and Thomas Funkhouser · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Coco-stuff: Thing and stuff classes in context
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Multimodal unsupervised image-to-image translation
Xun Huang, Ming-Yu Liu, Serge Belongie, and Jan Kautz · 2018
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Implicit maximum likelihood estimation
Ke Li and Jitendra Malik · 2018
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Ke Li, Tianhao Zhang, and Jitendra Malik · 2019
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Learning to predict layout-to-image conditional convolutions for semantic image synthesis
Xihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang, et al · 2019
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Semantic image synthesis with spatially-adaptive normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, and Jun-Yan Zhu · 2019
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Classification accuracy score for conditional generative models
Suman Ravuri and Oriol Vinyals · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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PA-GAN: Improving GAN training by progressive augmentation
Dan Zhang and Anna Khoreva · 2019
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Self-attention generative adversarial networks
Han Zhang, Ian J. Goodfellow, Dimitris N. Metaxas, and Augustus Odena · 2019
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Disentangled image generation through structured noise injection
Yazeed Alharbi and Peter Wonka · 2020
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Sesame: Semantic editing of scenes by adding, manipulating or erasing objects
Evangelos Ntavelis, Andrés Romero, Iason Kastanis, Luc Van Gool, and Radu Timofte · 2020
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A u-net based discriminator for generative adversarial networks
Edgar Schönfeld, Bernt Schiele, and Anna Khoreva · 2020
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Rethinking spatially-adaptive normalization
Zhentao Tan, Dongdong Chen, Qi Chu, Menglei Chai, Jing Liao, Mingming He, Lu Yuan, and Nenghai Yu · 2020
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Resnest: Split-attention networks
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R Manmatha, et al · 2020
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Semantically multi-modal image synthesis
Zhen Zhu, Zhiliang Xu, Ansheng You, and Xiang Bai · 2020
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