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Real-world image super-resolution (Real-ISR) aims to reconstruct high-resolution images from low-resolution inputs degraded by complex, unknown processes.
Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 1914
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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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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 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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Adam: A method for stochastic optimization
Diederik P Kingma · 2014
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A+: Adjusted anchored neighborhood regression for fast super-resolution
Radu Timofte, Vincent De Smet, and Luc Van Gool · 2015
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A feature-enriched completely blind image quality evaluator
Lin Zhang, Lei Zhang, and Alan C Bovik · 2015
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Generating images with perceptual similarity metrics based on deep networks
Alexey Dosovitskiy and Thomas Brox · 2016
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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
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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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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
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Image super-resolution using dense skip connections
Tong Tong, Gen Li, Xiejie Liu, and Qinquan Gao · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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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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Image quality assessment: Unifying structure and texture similarity
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P Simoncelli · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha 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
Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, and Liang Lin · 2020
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Toward interactive modulation for photo-realistic image restoration
Haoming Cai, Jingwen He, Yu Qiao, and Chao Dong · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Interactive multi-dimension modulation for image restoration
Jingwen He, Chao Dong, Yihao Liu, and Yu Qiao · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Musiq: Multi-scale image quality transformer
Junjie Ke, Qifei Wang, Yilin Wang, Peyman Milanfar, and Feng Yang · 2021
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Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Knowledge distillation in iterative generative models for improved sampling speed
Eric Luhman and Troy Luhman · 2021
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Tackling the generative learning trilemma with denoising diffusion gans
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2021
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Gan prior embedded network for blind face restoration in the wild
Tao Yang, Peiran Ren, Xuansong Xie, and Lei Zhang · 2021
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Designing a practical degradation model for deep blind image super-resolution
Kai Zhang, Jingyun Liang, Luc Van Gool, and Radu Timofte · 2021
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Content-aware scalable deep compressed sensing
Bin Chen and Jian Zhang · 2022
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Real-world blind super-resolution via feature matching with implicit high-resolution priors
Chaofeng Chen, Xinyu Shi, Yipeng Qin, Xiaoming Li, Xiaoguang Han, Tao Yang, and Shihui Guo · 2022
Cited alongside, same era.
Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Mobilediffusion: Subsecond text-to-image generation on mobile devices
Yang Zhao, Yanwu Xu, Zhisheng Xiao, and Tingbo Hou · 2023
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Edgefusion: On-device text-to-image generation
Thibault Castells, Hyoung-Kyu Song, Tairen Piao, Shinkook Choi, Bo-Kyeong Kim, Hanyoung Yim, Changgwun Lee, Jae Gon Kim, and Tae-Ho Kim · 2024
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Practical compact deep compressed sensing
Bin Chen and Jian Zhang · 2024
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Taming diffusion prior for image super-resolution with domain shift sdes
Qinpeng Cui, Yixuan Liu, Xinyi Zhang, Qiqi Bao, Zhongdao Wang, Qingmin Liao, Li Wang, Tian Lu, and Emad Barsoum · 2024
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Jingwen He, Wu Shi, Kai Chen, Lean Fu, and Chao Dong · 2022
Cited alongside, same era.
Srdiff: Single image super-resolution with diffusion probabilistic models
Haoying Li, Yifan Yang, Meng Chang, Shiqi Chen, Huajun Feng, Zhihai Xu, Qi Li, and Yueting Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Cited alongside, same era.
Diffusion-gan: Training gans with diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, and Mingyuan Zhou · 2022
Cited alongside, same era.
Maniqa: Multi-dimension attention network for no-reference image quality assessment
Sidi Yang, Tianhe Wu, Shuwei Shi, Shanshan Lao, Yuan Gong, Mingdeng Cao, Jiahao Wang, and Yujiu Yang · 2022
Cited alongside, same era.
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Swiftbrush v2: Make your one-step diffusion model better than its teacher
Trung Dao, Thuan Hoang Nguyen, Thanh Le, Duc Vu, Khoi Nguyen, Cuong Pham, and Anh Tran · 2024
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One step diffusion-based super-resolution with time-aware distillation
Xiao He, Huaao Tang, Zhijun Tu, Junchao Zhang, Kun Cheng, Hanting Chen, Yong Guo, Mingrui Zhu, Nannan Wang, Xinbo Gao, et al · 2024
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Jonathan Heek, Emiel Hoogeboom, and Tim Salimans · 2024
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Distilling diffusion models into conditional gans
Minguk Kang, Richard Zhang, Connelly Barnes, Sylvain Paris, Suha Kwak, Jaesik Park, Eli Shechtman, Jun-Yan Zhu, and Taesung Park · 2024
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Pagoda: Progressive growing of a one-step generator from a low-resolution diffusion teacher
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, and Stefano Ermon · 2024
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Tddsr: Single-step diffusion with two discriminators for super resolution
Sohwi Kim and Tae-Kyun Kim · 2024
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Sdxl-lightning: Progressive adversarial diffusion distillation
Shanchuan Lin, Anran Wang, and Xiao Yang · 2024
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2dquant: Low-bit post-training quantization for image super-resolution
Kai Liu, Haotong Qin, Yong Guo, Xin Yuan, Linghe Kong, Guihai Chen, and Yulun Zhang · 2024
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You only sample once: Taming one-step text-to-image synthesis by self-cooperative diffusion gans
Yihong Luo, Xiaolong Chen, and Jing Tang · 2024
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Deepcache: Accelerating diffusion models for free
Xinyin Ma, Gongfan Fang, and Xinchao Wang · 2024
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You only need one step: Fast super-resolution with stable diffusion via scale distillation
Mehdi Noroozi, Isma Hadji, Brais Martinez, Adrian Bulat, and Georgios Tzimiropoulos · 2024
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Xpsr: Cross-modal priors for diffusion-based image super-resolution
Yunpeng Qu, Kun Yuan, Kai Zhao, Qizhi Xie, Jinhua Hao, Ming Sun, and Chao Zhou · 2024
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Hyper-sd: Trajectory segmented consistency model for efficient image synthesis
Yuxi Ren, Xin Xia, Yanzuo Lu, Jiacheng Zhang, Jie Wu, Pan Xie, Xing Wang, and Xuefeng Xiao · 2024
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Fast high-resolution image synthesis with latent adversarial diffusion distillation
Axel Sauer, Frederic Boesel, Tim Dockhorn, Andreas Blattmann, Patrick Esser, and Robin Rombach · 2024
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Sdxs: Real-time one-step latent diffusion models with image conditions
Yuda Song, Zehao Sun, and Xuanwu Yin · 2024
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Seeclear: Semantic distillation enhances pixel condensation for video super-resolution
Qi Tang, Yao Zhao, Meiqin Liu, and Chao Yao · 2024
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Addsr: Accelerating diffusion-based blind super-resolution with adversarial diffusion distillation
Rui Xie, Ying Tai, Kai Zhang, Zhenyu Zhang, Jun Zhou, and Jian Yang · 2024
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Perflow: Piecewise rectified flow as universal plug-and-play accelerator
Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, and Jiashi Feng · 2024
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Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild
Fanghua Yu, Jinjin Gu, Zheyuan Li, Jinfan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, and Chao Dong · 2024
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Trajectory consistency distillation
Jianbin Zheng, Minghui Hu, Zhongyi Fan, Chaoyue Wang, Changxing Ding, Dacheng Tao, and Tat-Jen Cham · 2024
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Slimflow: Training smaller one-step diffusion models with rectified flow
Yuanzhi Zhu, Xingchao Liu, and Qiang Liu · 2024
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Invertible diffusion models for compressed sensing
Bin Chen, Zhenyu Zhang, Weiqi Li, Chen Zhao, Jiwen Yu, Shijie Zhao, Jie Chen, and Jian Zhang · 2025
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