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The recent use of diffusion prior, enhanced by pre-trained text-image models, has markedly elevated the performance of image super-resolution (SR).
Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik · 2012
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Generative adversarial networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Narain Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 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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Ntire 2017 challenge on single image super-resolution: Methods and results
Radu Timofte, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, and Lei Zhang · 2017
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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On the spectral bias of neural networks
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Dräxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, and Aaron C. Courville · 2018
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Recovering realistic texture in image super-resolution by deep spatial feature transform
Xintao Wang, K. Yu, Chao Dong, and Chen Change Loy · 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
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Toward real-world single image super-resolution: A new benchmark and a new model
Jianrui Cai, Hui Zeng, Hongwei Yong, Zisheng Cao, and Lei Zhang · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and P. Abbeel · 2020
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Real-world super-resolution via kernel estimation and noise injection
Xiaozhong Ji, Yun Cao, Ying Tai, Chengjie Wang, Jilin Li, and Feiyue Huang · 2020
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Focal frequency loss for image reconstruction and synthesis
Liming Jiang, Bo Dai, Wayne Wu, and Chen Change Loy · 2020
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Zoom-to-inpaint: Image inpainting with high-frequency details
Soo Ye Kim, Kfir Aberman, Nori Kanazawa, Rahul Garg, Neal Wadhwa, Huiwen Chang, Nikhil Karnad, Munchurl Kim, and Orly Liba · 2020
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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, et al · 2020
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Gshard: Scaling giant models with conditional computation and automatic sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen · 2020
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Srflow: Learning the super-resolution space with normalizing flow
Andreas Lugmayr, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Narain Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Component divide-and-conquer for real-world image super-resolution
Taming sparsely activated transformer with stochastic experts
Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Tuo Zhao, and Jianfeng Gao · 2021
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ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, and Ming-Yu Liu · 2022
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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam Shazeer · 2022
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Ernie-vilg 2.0: Improving text-to-image diffusion model with knowledge-enhanced mixture-of-denoising-experts
Zhida Feng, Zhenyu Zhang, Xintong Yu, Yewei Fang, Lanxin Li, Xuyi Chen, Yuxiang Lu, Jiaxiang Liu, Weichong Yin, Shi Feng, Yu Sun, Hao Tian, Hua Wu, and Haifeng Wang · 2022
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Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, and Liang Lin · 2020
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Ilvr: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon · 2021
Cited alongside, same era.
Musiq: Multi-scale image quality transformer
Junjie Ke, Qifei Wang, Yilin Wang, Peyman Milanfar, and Feng Yang · 2021
Cited alongside, same era.
On fast sampling of diffusion probabilistic models
Zhifeng Kong and Wei Ping · 2021
Cited alongside, same era.
Srdiff: Single image super-resolution with diffusion probabilistic models
Haoying Li, Yifan Yang, Meng Chang, Huajun Feng, Zhi hai Xu, Qi Li, and Yue ting Chen · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Scaling vision with sparse mixture of experts
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, and Neil Houlsby · 2021
Cited alongside, same era.
Hash layers for large sparse models
Stephen Roller, Sainbayar Sukhbaatar, Jason Weston, et al · 2021
Cited alongside, same era.
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
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Efficient and degradation-adaptive network for real-world image super-resolution
Jie Liang, Hui Zeng, and Lei Zhang · 2022
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Blind image super-resolution: A survey and beyond
Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, and Chao Dong · 2022
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Flexible style image super-resolution using conditional objective
Seung Ho Park, Young Su Moon, and Nam Ik Cho · 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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Generative diffusion prior for unified image restoration and enhancement
Ben Fei, Zhaoyang Lyu, Liang Pan, Junzhe Zhang, Weidong Yang, Tian jian Luo, Bo Zhang, and Bo Dai · 2023
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Catch missing details: Image reconstruction with frequency augmented variational autoencoder
Xinmiao Lin, Yikang Li, Jenhao Hsiao, Chiu Man Ho, and Yu Kong · 2023
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Cdpmsr: Conditional diffusion probabilistic models for single image super-resolution
Axi Niu, Kang Zhang, Trung Xuan Pham, Jinqiu Sun, Yu Zhu, In-So Kweon, and Yanning Zhang · 2023
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Denoising diffusion probabilistic models for robust image super-resolution in the wild
Hshmat Sahak, Daniel Watson, Chitwan Saharia, and David J. Fleet · 2023
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Exploiting diffusion prior for real-world image super-resolution
Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin C. K. Chan, and Chen Change Loy · 2023
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Raphael: Text-to-image generation via large mixture of diffusion paths
Zeyue Xue, Guanglu Song, Qiushan Guo, Boxiao Liu, Zhuofan Zong, Yu Liu, and Ping Luo · 2023
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Designing a better asymmetric vqgan for stablediffusion
Zixin Zhu, Xuelu Feng, Dongdong Chen, Jianmin Bao, Le Wang, Yinpeng Chen, Lu Yuan, and Gang Hua · 2023
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