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Given an incomplete image without additional constraint, image inpainting natively allows for multiple solutions as long as they appear plausible.
Image inpainting
Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester · 2000
Earlier work this paper cites.
Filling-in by joint interpolation of vector fields and gray levels
Coloma Ballester, Marcelo Bertalmio, Vicent Caselles, Guillermo Sapiro, and Joan Verdera · 2001
Earlier work this paper cites.
Simultaneous structure and texture image inpainting
Marcelo Bertalmio, Luminita Vese, Guillermo Sapiro, and Stanley Osher · 2003
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Fragment-based image completion
Iddo Drori, Daniel Cohen-Or, and Hezy Yeshurun · 2003
Earlier work this paper cites.
Region filling and object removal by exemplar-based image inpainting
Antonio Criminisi, Patrick Pérez, and Kentaro Toyama · 2004
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PatchMatch: A randomized correspondence algorithm for structural image editing
Connelly Barnes, Eli Shechtman, Adam Finkelstein, and Dan B. Goldman · 2009
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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ImageNet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, et al · 2015
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 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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Conditional image generation with PixelCNN decoders
Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, and Koray Kavukcuoglu · 2016
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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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Globally and locally consistent image completion
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 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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Fast generation for convolutional autoregressive models
Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark A. Hasegawa-Johnson, Roy H. Campbell, and Thomas S. Huang · 2017
Cited alongside, same era.
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P. Kingma · 2017
Cited alongside, same era.
Neural discrete representation learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
Cited alongside, same era.
Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
Cited alongside, same era.
The perception-distortion tradeoff
Yochai Blau and Tomer Michaeli · 2018
Cited alongside, same era.
EdgeConnect: Structure guided image inpainting using edge prediction
Kamyar Nazeri, Eric Ng, Tony Joseph, Faisal Z. Qureshi, and Mehran Ebrahimi · 2019
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Generating diverse high-fidelity images with VQ-VAE-2
Ali Razavi, Aaron van den Oord, and Oriol Vinyals · 2019
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StructureFlow: Image inpainting via structure-aware appearance flow
Yurui Ren, Xiaoming Yu, Ruonan Zhang, Thomas H. Li, Shan Liu, and Ge Li · 2019
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PEPSI: Fast image inpainting with parallel decoding network
Min-cheol Sagong, Yong-goo Shin, Seung-wook Kim, Seung Park, and Sung-jea Ko · 2019
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Foreground-aware image inpainting
Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, and Jiebo Luo · 2019
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Free-form image inpainting with gated convolution
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S. Huang · 2019
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PixelSNAIL: An improved autoregressive generative model
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, and Pieter Abbeel · 2018
Cited alongside, same era.
Image inpainting for irregular holes using partial convolutions
Guilin Liu, Fitsum A. Reda, Kevin J. Shih, Ting-Chun Wang, Andrew Tao, and Bryan Catanzaro · 2018
Cited alongside, same era.
Are GANs created equal? A large-scale study
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, and Olivier Bousquet · 2018
Cited alongside, same era.
Contextual-based image inpainting: Infer, match, and translate
Yuhang Song, Chao Yang, Zhe Lin, Xiaofeng Liu, Qin Huang, Hao Li, and C.-C. Jay Kuo · 2018
Cited alongside, same era.
SPG-Net: Segmentation prediction and guidance network for image inpainting
Yuhang Song, Chao Yang, Yeji Shen, Peng Wang, Qin Huang, and C.-C. Jay Kuo · 2018
Cited alongside, same era.
Shift-Net: Image inpainting via deep feature rearrangement
Zhaoyi Yan, Xiaoming Li, Mu Li, Wangmeng Zuo, and Shiguang Shan · 2018
Cited alongside, same era.
Generative image inpainting with contextual attention
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S. Huang · 2018
Cited alongside, same era.
Later among the works it cites.
Learning pyramid-context encoder network for high-quality image inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao, and Baining Guo · 2019
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Pluralistic image completion
Chuanxia Zheng, Tat-Jen Cham, and Jianfei Cai · 2019
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Guidance and evaluation: Semantic-aware image inpainting for mixed scenes
Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, and Shin’ichi Satoh · 2020
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Rethinking image inpainting via a mutual encoder-decoder with feature equalizations
Hongyu Liu, Bin Jiang, Yibing Song, Wei Huang, and Chao Yang · 2020
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E2I: Generative inpainting from edge to image
Shunxin Xu, Dong Liu, and Zhiwei Xiong · 2020
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Contextual residual aggregation for ultra high-resolution image inpainting
Zili Yi, Qiang Tang, Shekoofeh Azizi, Daesik Jang, and Zhan Xu · 2020
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UCTGAN: Diverse image inpainting based on unsupervised cross-space translation
Lei Zhao, Qihang Mo, Sihuan Lin, Zhizhong Wang, Zhiwen Zuo, Haibo Chen, Wei Xing, and Dongming Lu · 2020
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Learning oracle attention for high-fidelity face completion
Tong Zhou, Changxing Ding, Shaowen Lin, Xinchao Wang, and Dacheng Tao · 2020
Later among the works it cites.