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Image inpainting has made significant advances in recent years.
Image inpainting
Marcelo Bertalmío, Guillermo Sapiro, Vicent Caselles, and Coloma Ballester · 2000
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On the canny edge detector
Lijun Ding and Ardeshir Goshtasby · 2001
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Object removal by exemplar-based inpainting
Antonio Criminisi, Patrick Perez, and Kentaro Toyama · 2003
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Learning how to inpaint from global image statistics
Anat Levin, Assaf Zomet, and Yair Weiss · 2003
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Fields of experts: a framework for learning image priors
Stefan Roth and Michael J. Black · 2005
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Scene completion using millions of photographs
James Hays and Alexei A Efros · 2007
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Indoor segmentation and support inference from rgbd images
Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
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Describing textures in the wild
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, and Andrea Vedaldi · 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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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 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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Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2018
Earlier work this paper cites.
Learning to parse wireframes in images of man-made environments
Kun Huang, Yifan Wang, Zihan Zhou, Tianjiao Ding, Shenghua Gao, and Yi Ma · 2018
Earlier work this paper cites.
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.
Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer · 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.
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.
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.
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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Prior guided gan based semantic inpainting
Avisek Lahiri, Arnav Kumar Jain, Sanskar Agrawal, Pabitra Mitra, and Prabir Kumar Biswas · 2020
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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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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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On layer normalization in the transformer architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, and Tieyan Liu · 2020
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Positional encoding as spatial inductive bias in gans, 2020
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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.
Mask-predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer · 2019
Cited alongside, same era.
Axial attention in multidimensional transformers
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, and Tim Salimans · 2019
Cited alongside, same era.
Sc-fegan: Face editing generative adversarial network with user’s sketch and color
Youngjoo Jo and Jongyoul Park · 2019
Cited alongside, same era.
Edgeconnect: Structure guided image inpainting using edge prediction
Kamyar Nazeri, Eric Ng, Tony Joseph, Faisal Qureshi, and Mehran Ebrahimi · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2019
Cited alongside, same era.
Free-form image inpainting with gated convolution
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2019
Cited alongside, same era.
Rui Xu, Xintao Wang, Kai Chen, Bolei Zhou, and Chen Change Loy · 2020
Later among the works it cites.
Holistically-attracted wireframe parsing
Nan Xue, Tianfu Wu, Song Bai, Fudong Wang, Gui-Song Xia, Liangpei Zhang, and Philip HS Torr · 2020
Later among the works it cites.
Learning to incorporate structure knowledge for image inpainting
Jie Yang, Zhiquan Qi, and Yong Shi · 2020
Later among the works it cites.
Contextual residual aggregation for ultra high-resolution image inpainting
Zili Yi, Qiang Tang, Shekoofeh Azizi, Daesik Jang, and Zhan Xu · 2020
Later among the works it cites.
High-resolution image inpainting with iterative confidence feedback and guided upsampling
Yu Zeng, Zhe Lin, Jimei Yang, Jianming Zhang, Eli Shechtman, and Huchuan Lu · 2020
Later among the works it cites.
Learning a sketch tensor space for image inpainting of man-made scenes
Chenjie Cao and Yanwei Fu · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Image inpainting via conditional texture and structure dual generation
Xiefan Guo, Hongyu Yang, and Di Huang · 2021
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Colorization transformer, 2021
Manoj Kumar, Dirk Weissenborn, and Nal Kalchbrenner · 2021
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Infinitygan: Towards infinite-pixel image synthesis, 2021
Chieh Hubert Lin, Hsin-Ying Lee, Yen-Chi Cheng, Sergey Tulyakov, and Ming-Hsuan Yang · 2021
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Zero-shot text-to-image generation, 2021
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Resolution-robust large mask inpainting with fourier convolutions
Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, and Victor Lempitsky · 2021
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High-fidelity pluralistic image completion with transformers
Ziyu Wan, Jingbo Zhang, Dongdong Chen, and Jing Liao · 2021
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Early convolutions help transformers see better
Tete Xiao, Piotr Dollar, Mannat Singh, Eric Mintun, Trevor Darrell, and Ross Girshick · 2021
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Diverse image inpainting with bidirectional and autoregressive transformers
Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jianxiong Pan, Kaiwen Cui, Shijian Lu, Feiying Ma, Xuansong Xie, and Chunyan Miao · 2021
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Large scale image completion via co-modulated generative adversarial networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, and Yan Xu · 2021
Later among the works it cites.