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Image inpainting aims to fill in the missing pixels with visually coherent and semantically plausible content.
Layered representation for motion analysis
John YA Wang and Edward H Adelson · 1993
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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Image inpainting by patch propagation using patch sparsity
Zongben Xu and Jian Sun · 2010
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Microsoft coco: Common objects in context, 2015
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár · 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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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung · 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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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 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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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 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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Cr-fill: Generative image inpainting with auxiliary contextual reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu, and Vishal M Patel · 2021
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Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
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Universal guidance for diffusion models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2023
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Diffusion self-guidance for controllable image generation
Dave Epstein, Allan Jabri, Ben Poole, Alexei A Efros, and Aleksander Holynski · 2023
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Instruct-nerf2nerf: Editing 3d scenes with instructions
Ayaan Haque, Matthew Tancik, Alexei A Efros, Aleksander Holynski, and Angjoo Kanazawa · 2023
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Text2video-zero: Text-to-image diffusion models are zero-shot video generators
Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan, and Humphrey Shi · 2023
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Jonathan Ho and Tim Salimans · 2022
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
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Diffusion models already have a semantic latent space
Mingi Kwon, Jaeseok Jeong, and Youngjung Uh · 2022
Cited alongside, same era.
Mat: Mask-aware transformer for large hole image inpainting
Wenbo Li, Zhe Lin, Kun Zhou, Lu Qi, Yi Wang, and Jiaya Jia · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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Make-a-video: Text-to-video generation without text-video data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et al · 2022
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Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2023
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Poisson image editing
Patrick Pérez, Michel Gangnet, and Andrew Blake · 2023
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Dragdiffusion: Harnessing diffusion models for interactive point-based image editing
Yujun Shi, Chuhui Xue, Jiachun Pan, Wenqing Zhang, Vincent YF Tan, and Song Bai · 2023
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Zero-shot video editing using off-the-shelf image diffusion models
Wen Wang, Kangyang Xie, Zide Liu, Hao Chen, Yue Cao, Xinlong Wang, and Chunhua Shen · 2023
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Smartbrush: Text and shape guided object inpainting with diffusion model
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, and Kun Zhang · 2023
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Video diffusion models with local-global context guidance
Siyuan Yang, Lu Zhang, Yu Liu, Zhizhuo Jiang, and You He · 2023
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Inst-inpaint: Instructing to remove objects with diffusion models
Ahmet Burak Yildirim, Vedat Baday, Erkut Erdem, Aykut Erdem, and Aysegul Dundar · 2023
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