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Natural images captured by mobile devices often suffer from multiple types of degradation, such as noise, blur, and low light.
Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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Deblurgan: Blind motion deblurring using conditional adversarial networks
Orest Kupyn, Volodymyr Budzan, Mykola Mykhailych, Dmytro Mishkin, and Jiří Matas · 2018
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Noise2noise: Learning image restoration without clean data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, and Timo Aila · 2018
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Crafting a toolchain for image restoration by deep reinforcement learning
Ke Yu, Chao Dong, Liang Lin, 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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Jpeg artifacts reduction via deep convolutional sparse coding
Xueyang Fu, Zheng-Jun Zha, Feng Wu, Xinghao Ding, and John Paisley · 2019
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High-quality self-supervised deep image denoising
Samuli Laine, Tero Karras, Jaakko Lehtinen, and Timo Aila · 2019
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Residual non-local attention networks for image restoration
Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, and Yun Fu · 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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Image quality assessment for perceptual image restoration: A new dataset, benchmark and metric
Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy Ren, and Chao Dong · 2020
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Pipal: a large-scale image quality assessment dataset for perceptual image restoration
Gu Jinjin, Cai Haoming, Chen Haoyu, Ye Xiaoxing, Jimmy S Ren, and Dong Chao · 2020
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Ffa-net: Feature fusion attention network for single image dehazing
Xu Qin, Zhilin Wang, Yuanchao Bai, Xiaodong Xie, and Huizhu Jia · 2020
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Unpaired learning of deep image denoising
Xiaohe Wu, Ming Liu, Yue Cao, Dongwei Ren, and Wangmeng Zuo · 2020
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Rethinking coarse-to-fine approach in single image deblurring
Sung-Jin Cho, Seo-Won Ji, Jun-Pyo Hong, Seung-Won Jung, and Sung-Jea Ko · 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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Towards flexible blind jpeg artifacts removal
Jiaxi Jiang, Kai Zhang, and Radu Timofte · 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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Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 2021
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Contrastive learning for compact single image dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie, and Lizhuang Ma · 2021
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Snowformer: Context interaction transformer with scale-awareness for single image desnowing
Sixiang Chen, Tian Ye, Yun Liu, and Erkang Chen · 2022
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Snowformer: Context interaction transformer with scale-awareness for single image desnowing
Sixiang Chen, Tian Ye, Yun Liu, and Erkang Chen · 2022
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Xydeblur: Divide and conquer for single image deblurring
Seo-Won Ji, Jeongmin Lee, Seung-Wook Kim, Jun-Pyo Hong, Seung-Jin Baek, Seung-Won Jung, and Sung-Jea Ko · 2022
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All-in-one image restoration for unknown corruption
Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, and Xi Peng · 2022
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Tape: Task-agnostic prior embedding for image restoration
Lin Liu, Lingxi Xie, Xiaopeng Zhang, Shanxin Yuan, Xiangyu Chen, Wengang Zhou, Houqiang Li, and Qi Tian · 2022
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Blind2unblind: Self-supervised image denoising with visible blind spots
Zejin Wang, Jiazheng Liu, Guoqing Li, and Hua Han · 2022
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Deblurring via stochastic refinement
Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, and Peyman Milanfar · 2022
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Restormer: Efficient transformer for high-resolution image restoration
Prompt-in-prompt learning for universal image restoration
Zilong Li, Yiming Lei, Chenglong Ma, Junping Zhang, and Hongming Shan · 2023
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Diffbir: Towards blind image restoration with generative diffusion prior
Xinqi Lin, Jingwen He, Ziyan Chen, Zhaoyang Lyu, Ben Fei, Bo Dai, Wanli Ouyang, Yu Qiao, and Chao Dong · 2023
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Visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Controlling vision-language models for universal image restoration
Ziwei Luo, Fredrik K Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B Schön · 2023
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All-in-one image restoration for unknown degradations using adaptive discriminative filters for specific degradations
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Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
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Idr: Self-supervised image denoising via iterative data refinement
Yi Zhang, Dasong Li, Ka Lung Law, Xiaogang Wang, Hongwei Qin, and Hongsheng Li · 2022
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Yuang Ai, Huaibo Huang, Xiaoqiang Zhou, Jiexiang Wang, and Ran He · 2023
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Retinexformer: One-stage retinex-based transformer for low-light image enhancement
Yuanhao Cai, Hao Bian, Jing Lin, Haoqian Wang, Radu Timofte, and Yulun Zhang · 2023
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Masked image training for generalizable deep image denoising
Haoyu Chen, Jinjin Gu, Yihao Liu, Salma Abdel Magid, Chao Dong, Qiong Wang, Hanspeter Pfister, and Lei Zhu · 2023
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Snow removal in video: A new dataset and a novel method
Haoyu Chen, Jingjing Ren, Jinjin Gu, Hongtao Wu, Xuequan Lu, Haoming Cai, and Lei Zhu · 2023
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Minigpt-v2: large language model as a unified interface for vision-language multi-task learning
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechun Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, and Mohamed Elhoseiny · 2023
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Kosmos-2: Grounding multimodal large language models to the world
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, and Furu Wei · 2023
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Promptir: Prompting for all-in-one blind image restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, and Fahad Shahbaz Khan · 2023
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Glamm: Pixel grounding large multimodal model
Hanoona Rasheed, Muhammad Maaz, Sahal Shaji, Abdelrahman Shaker, Salman Khan, Hisham Cholakkal, Rao M Anwer, Erix Xing, Ming-Hsuan Yang, and Fahad S Khan · 2023
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Multiscale structure guided diffusion for image deblurring
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Coser: Bridging image and language for cognitive super-resolution
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Llama: Open and efficient foundation language models
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Exploiting diffusion prior for real-world image super-resolution
Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin CK Chan, and Chen Change Loy · 2023
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Clarity chatgpt: An interactive and adaptive processing system for image restoration and enhancement
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Seesr: Towards semantics-aware real-world image super-resolution
Rongyuan Wu, Tao Yang, Lingchen Sun, Zhengqiang Zhang, Shuai Li, and Lei Zhang · 2023
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Ridcp: Revitalizing real image dehazing via high-quality codebook priors
Ruiqi Wu, Zhengpeng Duan, Chunle Guo, Zhi Chai, and Chongyi Li · 2023
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Low-res leads the way: Improving generalization for super-resolution by self-supervised learning
Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Haoze Sun, Xueyi Zou, Youliang Yan, Zhensong Zhang, and Lei Zhu · 2024
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High-quality image restoration following human instructions
Marcos V Conde, Gregor Geigle, and Radu Timofte · 2024
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Llmra: Multi-modal large language model based restoration assistant
Xiaoyu Jin, Yuan Shi, Bin Xia, and Wenming Yang · 2024
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Towards effective multiple-in-one image restoration: A sequential and prompt learning strategy
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Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild
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Revisiting zeroth-order optimization for memory-efficient llm fine-tuning: A benchmark
Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D Lee, Wotao Yin, Mingyi Hong, et al · 2024
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