Fetching the paper…
Reading the bibliography…
Recent advancements in all-in-one image restoration models have revolutionized the ability to address diverse degradations through a unified framework.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik · 2001
Earlier work this paper cites.
Contour detection and hierarchical image segmentation
Pablo Arbelaez, Michael Maire, Charless Fowlkes, and Jitendra Malik · 2010
Earlier work this paper cites.
Augmented reality for restoration/reconstruction of artefacts with artistic or historical value
Giovanni Saggio, Davide Borra, et al · 2011
Earlier work this paper cites.
Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
Earlier work this paper cites.
Virtual restoration of deteriorated religious heritage objects using augmented reality technologies
Florin Girbacia, Silviu Butnariu, Alex Petre Orman, and Cristian Cezar Postelnicu · 2013
Earlier work this paper cites.
U-Net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Non-local image dehazing
Dana Berman and Shai Avidan · 2016
Earlier work this paper cites.
Dehazenet: An end-to-end system for single image haze removal
Bolun Cai, Xiangmin Xu, Kui Jia, Chunmei Qing, and Dacheng Tao · 2016
Earlier work this paper cites.
Waterloo exploration database: New challenges for image quality assessment models
Kede Ma, Zhengfang Duanmu, Qingbo Wu, Zhou Wang, Hongwei Yong, Hongliang Li, and Lei Zhang · 2016
Earlier work this paper cites.
Blind image deblurring using dark channel prior
Jinshan Pan, Deqing Sun, Hans Pfister, and Ming-Hsuan Yang · 2016
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2017
Earlier work this paper cites.
Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Outrageously large neural networks: The sparsely-gated mixture-of-experts layer, 2017
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
Earlier work this paper cites.
Memnet: A persistent memory network for image restoration
Ying Tai, Jian Yang, Xiaoming Liu, and Chunyan Xu · 2017
Earlier work this paper cites.
Learning deep cnn denoiser prior for image restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, and Lei Zhang · 2017
Earlier work this paper cites.
Noise2noise: Learning image restoration without clean data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, and Timo Aila · 2018
Earlier work this paper cites.
Benchmarking single-image dehazing and beyond
Boyi Li, Wenqi Ren, Dengpan Fu, Dacheng Tao, Dan Feng, Wenjun Zeng, and Zhangyang Wang · 2018
Earlier work this paper cites.
Gated fusion network for single image dehazing
Wenqi Ren, Lin Ma, Jiawei Zhang, Jinshan Pan, Xiaochun Cao, Wei Liu, and Ming-Hsuan Yang · 2018
Earlier work this paper cites.
Deep retinex decomposition for low-light enhancement
Chen Wei, Wenjing Wang, Wenhan Yang, and Jiaying Liu · 2018
Earlier work this paper cites.
A general decoupled learning framework for parameterized image operators
Qingnan Fan, Dongdong Chen, Lu Yuan, Gang Hua, Nenghai Yu, and Baoquan Chen · 2019
Earlier work this paper cites.
Dynamic scene deblurring with parameter selective sharing and nested skip connections
Hongyun Gao, Xin Tao, Xiaoyong Shen, and Jiaya Jia · 2019
Earlier work this paper cites.
Enhanced pix2pix dehazing network
Yanyun Qu, Yizi Chen, Jingying Huang, and Yuan Xie · 2019
Earlier work this paper cites.
Progressive image deraining networks: A better and simpler baseline
Dongwei Ren, Wangmeng Zuo, Qinghua Hu, Pengfei Zhu, and Deyu Meng · 2019
Cited alongside, same era.
Uncertainty guided multi-scale residual learning-using a cycle spinning cnn for single image de-raining
Rajeev Yasarla and Vishal M Patel · 2019
Cited alongside, same era.
Residual non-local attention networks for image restoration
Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, and Yun Fu · 2019
Cited alongside, same era.
An application performance optimization model of mobile augmented reality based on hd restoration
Xin Dang, Hai Wang, Jie Ren, and Le Chen · 2020
Cited alongside, same era.
Fd-gan: Generative adversarial networks with fusion-discriminator for single image dehazing
Yu Dong, Yihao Liu, He Zhang, Shifeng Chen, and Yu Qiao · 2020
Cited alongside, same era.
Mixture-of-experts with expert choice routing
Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew M Dai, Quoc V Le, James Laudon, et al · 2022
Later among the works it cites.
Always clear days: Degradation type and severity aware all-in-one adverse weather removal
Yu-Wei Chen and Soo-Chang Pei · 2023
Later among the works it cites.
Autodir: Automatic all-in-one image restoration with latent diffusion
Yitong Jiang, Zhaoyang Zhang, Tianfan Xue, and Jinwei Gu · 2023
Later among the works it cites.
Efficient frequency domain-based transformers for high-quality image deblurring
Lingshun Kong, Jiangxin Dong, Jianjun Ge, Mingqiang Li, and Jinshan Pan · 2023
Later among the works it cites.
Prompt-in-prompt learning for universal image restoration
Zilong Li, Yiming Lei, Chenglong Ma, Junping Zhang, and Hongming Shan · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Multi-scale progressive fusion network for single image deraining
Kui Jiang, Zhongyuan Wang, Peng Yi, Chen Chen, Baojin Huang, Yimin Luo, Jiayi Ma, and Junjun Jiang · 2020
Cited alongside, same era.
Single image dehazing via multi-scale convolutional neural networks with holistic edges
Wenqi Ren, Jinshan Pan, Hua Zhang, Xiaochun Cao, and Ming-Hsuan Yang · 2020
Cited alongside, same era.
Image denoising using deep cnn with batch renormalization
Chunwei Tian, Yong Xu, and Wangmeng Zuo · 2020
Cited alongside, same era.
Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, and Baining Guo · 2020
Cited alongside, same era.
Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
Cited alongside, same era.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 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.
Later among the works it cites.
Wm-moe: Weather-aware multi-scale mixture-of-experts for blind adverse weather removal
Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, and Shanghang Zhang · 2023
Later among the works it cites.
Promptir: Prompting for all-in-one image restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, and Fahad Khan · 2023
Later among the works it cites.
Promptrestorer: A prompting image restoration method with degradation perception
Cong Wang, Jinshan Pan, Wei Wang, Jiangxin Dong, Mengzhu Wang, Yakun Ju, and Junyang Chen · 2023
Later among the works it cites.
Ingredient-oriented multi-degradation learning for image restoration
Jinghao Zhang, Jie Huang, Mingde Yao, Zizheng Yang, Hu Yu, Man Zhou, and Feng Zhao · 2023
Later among the works it cites.
Comprehensive and delicate: An efficient transformer for image restoration
Haiyu Zhao, Yuanbiao Gou, Boyun Li, Dezhong Peng, Jiancheng Lv, and Xi Peng · 2023
Later among the works it cites.
Learning weather-general and weather-specific features for image restoration under multiple adverse weather conditions
Yurui Zhu, Tianyu Wang, Xueyang Fu, Xuanyu Yang, Xin Guo, Jifeng Dai, Yu Qiao, and Xiaowei Hu · 2023
Later among the works it cites.
Restoring vision in adverse weather conditions with patch-based denoising diffusion models
Ozan Özdenizci and Robert Legenstein · 2023
Later among the works it cites.
Multimodal prompt perceiver: Empower adaptiveness generalizability and fidelity for all-in-one image restoration
Yuang Ai, Huaibo Huang, Xiaoqiang Zhou, Jiexiang Wang, and Ran He · 2024
Closest in time.
Instructir: High-quality image restoration following human instructions
Marcos V Conde, Gregor Geigle, and Radu Timofte · 2024
Closest in time.
Uniprocessor: A text-induced unified low-level image processor
Huiyu Duan, Xiongkuo Min, Sijing Wu, Wei Shen, and Guangtao Zhai · 2024
Closest in time.
Controlling vision-language models for multi-task image restoration
Ziwei Luo, Fredrik K Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B Schön · 2024
Closest in time.
From sparse to soft mixtures of experts
Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, and Neil Houlsby · 2024
Closest in time.
Mixture-of-depths: Dynamically allocating compute in transformer-based language models, 2024
David Raposo, Sam Ritter, Blake Richards, Timothy Lillicrap, Peter Conway Humphreys, and Adam Santoro · 2024
Closest in time.
Gridformer: Residual dense transformer with grid structure for image restoration in adverse weather conditions
Tao Wang, Kaihao Zhang, Ziqian Shao, Wenhan Luo, Bjorn Stenger, Tong Lu, Tae-Kyun Kim, Wei Liu, and Hongdong Li · 2024
Closest in time.
Harmony in diversity: Improving all-in-one image restoration via multi-task collaboration
Gang Wu, Junjun Jiang, Kui Jiang, and Xianming Liu · 2024
Closest in time.
Multi-expert adaptive selection: Task-balancing for all-in-one image restoration
Xiaoyan Yu, Shen Zhou, Huafeng Li, and Liehuang Zhu · 2024
Closest in time.