Fetching the paper…
Reading the bibliography…
Recently, learning-based algorithms for image inpainting achieve remarkable progress dealing with squared or irregular holes.
Chuanxia Zheng, Tat-Jen Cham, and Jianfei Cai. 2019 · 1903
Earlier work this paper cites.
Semantic Image Inpainting with Progressive Generative Networks. In 2018 ACM Multimedia Conference on Multimedia Conference . ACM, 1939–1947
Haoran Zhang, Zhenzhen Hu, Changzhi Luo, Wangmeng Zuo, and Meng Wang. 2018 · 1947
Earlier work this paper cites.
Structural Inpainting. In Proceedings of the 26th ACM International Conference on Multimedia (MM ’18) . ACM, New York, NY, USA, 1948–1956
Huy V. Vo, Ngoc Q. K. Duong, and Patrick Pérez. 2018 · 1956
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. 2000 · 2000
Earlier work this paper cites.
Image inpainting. In Proceedings of the 27th annual conference on Computer graphics and interactive techniques . ACM Press/Addison-Wesley Publishing Co., 417–424
Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester. 2000 · 2000
Earlier work this paper cites.
Digital inpainting based on the Mumford–Shah–Euler image model
Selim Esedoglu and Jianhong Shen. 2002 · 2002
Earlier work this paper cites.
Simultaneous structure and texture image inpainting
Marcelo Bertalmio, Luminita Vese, Guillermo Sapiro, and Stanley Osher. 2003 · 2003
Earlier work this paper cites.
Fragment-based image completion. In ACM Transactions on graphics (TOG) , Vol. 22. ACM, 303–312
Iddo Drori, Daniel Cohen-Or, and Hezy Yeshurun. 2003 · 2003
Earlier work this paper cites.
Learning how to inpaint from global image statistics. In null . IEEE, 305
Anat Levin, Assaf Zomet, and Yair Weiss. 2003 · 2003
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, Eero P Simoncelli, et al · 2004
Earlier work this paper cites.
Image completion with structure propagation. In ACM Transactions on Graphics (ToG) , Vol. 24. ACM, 861–868
Jian Sun, Lu Yuan, Jiaya Jia, and Heung-Yeung Shum. 2005 · 2005
Earlier work this paper cites.
Image compression with edge-based inpainting
Dong Liu, Xiaoyan Sun, Feng Wu, Shipeng Li, and Ya-Qin Zhang. 2007 · 2007
Earlier work this paper cites.
PatchMatch: A randomized correspondence algorithm for structural image editing. In ACM Transactions on Graphics (ToG) , Vol. 28. ACM, 24
Connelly Barnes, Eli Shechtman, Adam Finkelstein, and Dan B Goldman. 2009 · 2009
Cited alongside, same era.
Image inpainting by patch propagation using patch sparsity
Zongben Xu and Jian Sun. 2010 · 2010
Cited alongside, same era.
Image melding: Combining inconsistent images using patch-based synthesis
Soheil Darabi, Eli Shechtman, Connelly Barnes, Dan B Goldman, and Pradeep Sen. 2012 · 2012
Cited alongside, same era.
Generative adversarial nets. In Advances in neural information processing systems . 2672–2680
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Image completion using planar structure guidance
Jia-Bin Huang, Sing Bing Kang, Narendra Ahuja, and Johannes Kopf. 2014 · 2014
Cited alongside, same era.
Globally and locally consistent image completion
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa. 2017 · 2017
Later among the works it cites.
Image-to-image translation with conditional adversarial networks. In Proceedings of the IEEE conference on computer vision and pattern recognition . 1125–1134
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros. 2017 · 2017
Later among the works it cites.
Enhanced deep residual networks for single image super-resolution. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops . 136–144
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee. 2017 · 2017
Later among the works it cites.
Semantic image inpainting with deep generative models. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 5485–5493
Raymond A Yeh, Chen Chen, Teck Yian Lim, Alexander G Schwing, Mark Hasegawa-Johnson, and Minh N Do. 2017 · 2017
Later among the works it cites.
Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Karen Simonyan and Andrew Zisserman. 2014 · 2014
Cited alongside, same era.
Deep learning face attributes in the wild. In Proceedings of the IEEE international conference on computer vision . 3730–3738
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang. 2015 · 2015
Cited alongside, same era.
Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution. In European conference on computer vision . Springer, 694–711
Justin Johnson, Alexandre Alahi, and Li Fei-Fei. 2016 · 2016
Cited alongside, same era.
Accurate image super-resolution using very deep convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition . 1646–1654
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee. 2016 · 2016
Cited alongside, same era.
Context encoders: Feature learning by inpainting. In Proceedings of the IEEE conference on computer vision and pattern recognition . 2536–2544
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros. 2016 · 2016
Cited alongside, same era.
Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky. 2016 · 2016
Cited alongside, same era.
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang. 2017 · 2017
Later among the works it cites.
Places: A 10 million Image Database for Scene Recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba. 2017 · 2017
Later among the works it cites.
Image inpainting for irregular holes using partial convolutions. In Proceedings of the European Conference on Computer Vision (ECCV) . 85–100
Guilin Liu, Fitsum A Reda, Kevin J Shih, Ting-Chun Wang, Andrew Tao, and Bryan Catanzaro. 2018 · 2018
Later among the works it cites.
Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida. 2018 · 2018
Later among the works it cites.
Generative image inpainting with contextual attention. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 5505–5514
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang. 2018 · 2018
Later among the works it cites.
EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning
Kamyar Nazeri, Eric Ng, Tony Joseph, Faisal Qureshi, and Mehran Ebrahimi. 2019 · 2019
Closest in time.
Deep High-Resolution Representation Learning for Human Pose Estimation
Ke Sun, Bin Xiao, Dong Liu, and Jingdong Wang. 2019 · 2019
Closest in time.
Foreground-aware Image Inpainting
Wei Xiong, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, and Jiebo Luo. 2019 · 2019
Closest in time.