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Despite the existence of numerous colorization methods, several limitations still exist, such as lack of user interaction, inflexibility in local colorization, unnatural color rendering, insufficient color variation, and color overflow.
Measuring colorfulness in natural images
David Hasler and Sabine E Suesstrunk · 2003
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Colorization using optimization
Anat Levin, Dani Lischinski, and Yair Weiss · 2004
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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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Natural image colorization
Qing Luan, Fang Wen, Daniel Cohen-Or, Lin Liang, Ying-Qing Xu, and Heung-Yeung Shum · 2007
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Scope of validity of psnr in image/video quality assessment
Quan Huynh-Thu and Mohammed Ghanbari · 2008
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Slic superpixels compared to state-of-the-art superpixel methods
Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk · 2012
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Deep colorization
Zezhou Cheng, Qingxiong Yang, and Bin Sheng · 2015
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Deepprop: Extracting deep features from a single image for edit propagation
Yuki Endo, Satoshi Iizuka, Yoshihiro Kanamori, and Jun Mitani · 2016
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Learning representations for automatic colorization
Gustav Larsson, Michael Maire, and Gregory Shakhnarovich · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 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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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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Real-time user-guided image colorization with learned deep priors
Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S Lin, Tianhe Yu, and Alexei A Efros · 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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Language-based image editing with recurrent attentive models
Jianbo Chen, Yelong Shen, Jianfeng Gao, Jingjing Liu, and Xiaodong Liu · 2018
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Deep exemplar-based colorization
Mingming He, Dongdong Chen, Jing Liao, Pedro V Sander, and Lu Yuan · 2018
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Learning to color from language
Varun Manjunatha, Mohit Iyyer, Jordan Boyd-Graber, and Larry Davis · 2018
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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.
https://github.com/jantic/DeOldify , 2019
Deoldify · 2019
Cited alongside, same era.
Interactive deep colorization using simultaneous global and local inputs
Yi Xiao, Peiyao Zhou, Yan Zheng, and Chi-Sing Leung · 2019
Cited alongside, same era.
Deep exemplar-based video colorization
Bo Zhang, Mingming He, Jing Liao, Pedro V Sander, Lu Yuan, Amine Bermak, and Dong Chen · 2019
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Unicolor: A unified framework for multi-modal colorization with transformer
Zhitong Huang, Nanxuan Zhao, and Jing Liao · 2022
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Colorformer: Image colorization via color memory assisted hybrid-attention transformer
Xiaozhong Ji, Boyuan Jiang, Donghao Luo, Guangpin Tao, Wenqing Chu, Zhifeng Xie, Chengjie Wang, and Ying Tai · 2022
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Bigcolor: Colorization using a generative color prior for natural images
Geonung Kim, Kyoungkook Kang, Seongtae Kim, Hwayoon Lee, Sehoon Kim, Jonghyun Kim, Seung-Hwan Baek, and Sunghyun Cho · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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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 · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Instance-aware image colorization
Jheng-Wei Su, Hung-Kuo Chu, and Jia-Bin Huang · 2020
Cited alongside, same era.
Chromagan: Adversarial picture colorization with semantic class distribution
Patricia Vitoria, Lara Raad, and Coloma Ballester · 2020
Cited alongside, same era.
Pixelated semantic colorization
Jiaojiao Zhao, Jungong Han, Ling Shao, and Cees GM Snoek · 2020
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 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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L-code: language-based colorization using color-object decoupled conditions
Shuchen Weng, Hao Wu, Zheng Chang, Jiajun Tang, Si Li, and Boxin Shi · 2022
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Disentangled image colorization via global anchors
Menghan Xia, Wenbo Hu, Tien-Tsin Wong, and Jue Wang · 2022
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L-cad: Language-based colorization with any-level descriptions
Zheng Chang, Shuchen Weng, Peixuan Zhang, Yu Li, Si Li, and Boxin Shi · 2023
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Improving sample quality of diffusion models using self-attention guidance
Susung Hong, Gyuseong Lee, Wooseok Jang, and Seungryong Kim · 2023
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Composer: Creative and controllable image synthesis with composable conditions
Lianghua Huang, Di Chen, Yu Liu, Yujun Shen, Deli Zhao, and Jingren Zhou · 2023
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Ddcolor: Towards photo-realistic image colorization via dual decoders
Xiaoyang Kang, Tao Yang, Wenqi Ouyang, Peiran Ren, Lingzhi Li, and Xuansong Xie · 2023
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Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2023
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Lightglue: Local feature matching at light speed
Philipp Lindenberger, Paul-Edouard Sarlin, and Marc Pollefeys · 2023
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icolorit: Towards propagating local hints to the right region in interactive colorization by leveraging vision transformer
Jooyeol Yun, Sanghyeon Lee, Minho Park, and Jaegul Choo · 2023
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Diffusing colors: Image colorization with text guided diffusion
Nir Zabari, Aharon Azulay, Alexey Gorkor, Tavi Halperin, and Ohad Fried · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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