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This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of…

This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters,…

This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript focuses on the competition set-up, the proposed methods and…

This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are…

This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting, where paired true high and low-resolution images are…

This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. The task of this challenge was to develop an…

This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR) do not go beyond factor 4. Missing information can be…

This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018. In contrast to previous SR challenges, our…

Computer Vision and Pattern Recognition · Computer Science 2019-06-03 Yochai Blau , Roey Mechrez , Radu Timofte , Tomer Michaeli , Lihi Zelnik-Manor

This paper reviews the AIM 2020 challenge on extreme image inpainting. This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image…

Computer Vision and Pattern Recognition · Computer Science 2020-10-05 Evangelos Ntavelis , Andrés Romero , Siavash Bigdeli , Radu Timofte

This paper summarizes the 3rd NTIRE challenge on stereo image super-resolution (SR) with a focus on new solutions and results. The task of this challenge is to super-resolve a low-resolution stereo image pair to a high-resolution one with a…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Longguang Wang , Yulan Guo , Juncheng Li , Hongda Liu , Yang Zhao , Yingqian Wang , Zhi Jin , Shuhang Gu , Radu Timofte

This paper reviews the AIM 2025 Efficient Real-World Deblurring using Single Images Challenge, which aims to advance in efficient real-blur restoration. The challenge is based on a new test set based on the well known RSBlur dataset. Pairs…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Daniel Feijoo , Paula Garrido-Mellado , Marcos V. Conde , Jaesung Rim , Alvaro Garcia , Sunghyun Cho , Radu Timofte

In this paper, we summarize the 1st NTIRE challenge on stereo image super-resolution (restoration of rich details in a pair of low-resolution stereo images) with a focus on new solutions and results. This challenge has 1 track aiming at the…

Computer Vision and Pattern Recognition · Computer Science 2022-04-21 Longguang Wang , Yulan Guo , Yingqian Wang , Juncheng Li , Shuhang Gu , Radu Timofte

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track~2 targets the super-resolution of…

This paper presents the NTIRE 2026 image super-resolution ($\times$4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to reconstruct high-resolution (HR) images from low-resolution…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Zheng Chen , Kai Liu , Jingkai Wang , Xianglong Yan , Jianze Li , Ziqing Zhang , Jue Gong , Jiatong Li , Lei Sun , Xiaoyang Liu , Radu Timofte , Yulun Zhang , Jihye Park , Yoonjin Im , Hyungju Chun , Hyunhee Park , MinKyu Park , Zheng Xie , Xiangyu Kong , Weijun Yuan , Zhan Li , Qiurong Song , Luen Zhu , Fengkai Zhang , Xinzhe Zhu , Junyang Chen , Congyu Wang , Yixin Yang , Zhaorun Zhou , Jiangxin Dong , Jinshan Pan , Shengwei Wang , Jiajie Ou , Baiang Li , Sizhuo Ma , Qiang Gao , Jusheng Zhang , Jian Wang , Keze Wang , Yijiao Liu , Yingsi Chen , Hui Li , Yu Wang , Congchao Zhu , Saeed Ahmad , Ik Hyun Lee , Jun Young Park , Ji Hwan Yoon , Kainan Yan , Zian Wang , Weibo Wang , Shihao Zou , Chao Dong , Wei Zhou , Linfeng Li , Jaeseong Lee , Jaeho Chae , Jinwoo Kim , Seonjoo Kim , Yucong Hong , Zhenming Yan , Junye Chen , Ruize Han , Song Wang , Yuxuan Jiang , Chengxi Zeng , Tianhao Peng , Fan Zhang , David Bull , Tongyao Mu , Qiong Cao , Yifan Wang , Youwei Pan , Leilei Cao , Xiaoping Peng , Wei Deng , Yifei Chen , Wenbo Xiong , Xian Hu , Yuxin Zhang , Xiaoyun Cheng , Yang Ji , Zonghao Chen , Zhihao Xue , Junqin Hu , Nihal Kumar , Snehal Singh Tomar , Klaus Mueller , Surya Vashisth , Prateek Shaily , Jayant Kumar , Hardik Sharma , Ashish Negi , Sachin Chaudhary , Akshay Dudhane , Praful Hambarde , Amit Shukla , Shijun Shi , Jiangning Zhang , Yong Liu , Kai Hu , Jing Xu , Xianfang Zeng , Amitesh M , Hariharan S , Chia-Ming Lee , Yu-Fan Lin , Chih-Chung Hsu , Nishalini K , Sreenath K A , Bilel Benjdira , Anas M. Ali , Wadii Boulila , Shuling Zheng , Zhiheng Fu , Feng Zhang , Zhanglu Chen , Boyang Yao , Nikhil Pathak , Aagam Jain , Milan Kumar , Kishor Upla , Vivek Chavda , Sarang N S , Raghavendra Ramachandra , Zhipeng Zhang , Qi Wang , Shiyu Wang , Jiachen Tu , Guoyi Xu , Yaoxin Jiang , Jiajia Liu , Yaokun Shi , Yuqi Li , Chuanguang Yang , Weilun Feng , Zhuzhi Hong , Hao Wu , Junming Liu , Yingli Tian , Amish Bhushan Kulkarni , Tejas R R Shet , Saakshi M Vernekar , Nikhil Akalwadi , Kaushik Mallibhat , Ramesh Ashok Tabib , Uma Mudenagudi , Yuwen Pan , Tianrun Chen , Deyi Ji , Qi Zhu , Lanyun Zhu , Heyan Zhangyi

Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIRE 2021 Challenge on Video Super-Resolution. We present…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Sanghyun Son , Suyoung Lee , Seungjun Nah , Radu Timofte , Kyoung Mu Lee

We introduce the AIM 2025 Real-World RAW Image Denoising Challenge, aiming to advance efficient and effective denoising techniques grounded in data synthesis. The competition is built upon a newly established evaluation benchmark featuring…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Feiran Li , Jiacheng Li , Marcos V. Conde , Beril Besbinar , Vlad Hosu , Daisuke Iso , Radu Timofte

This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating corresponding high-resolution (HR) images, magnified by a…

This paper presents the NTIRE 2025 image super-resolution ($\times$4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to recover high-resolution (HR) images from low-resolution (LR)…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Zheng Chen , Kai Liu , Jue Gong , Jingkai Wang , Lei Sun , Zongwei Wu , Radu Timofte , Yulun Zhang , Xiangyu Kong , Xiaoxuan Yu , Hyunhee Park , Suejin Han , Hakjae Jeon , Dafeng Zhang , Hyung-Ju Chun , Donghun Ryou , Inju Ha , Bohyung Han , Lu Zhao , Yuyi Zhang , Pengyu Yan , Jiawei Hu , Pengwei Liu , Fengjun Guo , Hongyuan Yu , Pufan Xu , Zhijuan Huang , Shuyuan Cui , Peng Guo , Jiahui Liu , Dongkai Zhang , Heng Zhang , Huiyuan Fu , Huadong Ma , Yanhui Guo , Sisi Tian , Xin Liu , Jinwen Liang , Jie Liu , Jie Tang , Gangshan Wu , Zeyu Xiao , Zhuoyuan Li , Yinxiang Zhang , Wenxuan Cai , Vijayalaxmi Ashok Aralikatti , Nikhil Akalwadi , G Gyaneshwar Rao , Chaitra Desai , Ramesh Ashok Tabib , Uma Mudenagudi , Marcos V. Conde , Alejandro Merino , Bruno Longarela , Javier Abad , Weijun Yuan , Zhan Li , Zhanglu Chen , Boyang Yao , Aagam Jain , Milan Kumar Singh , Ankit Kumar , Shubh Kawa , Divyavardhan Singh , Anjali Sarvaiya , Kishor Upla , Raghavendra Ramachandra , Chia-Ming Lee , Yu-Fan Lin , Chih-Chung Hsu , Risheek V Hiremath , Yashaswini Palani , Yuxuan Jiang , Qiang Zhu , Siyue Teng , Fan Zhang , Shuyuan Zhu , Bing Zeng , David Bull , Jingwei Liao , Yuqing Yang , Wenda Shao , Junyi Zhao , Qisheng Xu , Kele Xu , Sunder Ali Khowaja , Ik Hyun Lee , Snehal Singh Tomar , Rajarshi Ray , Klaus Mueller , Sachin Chaudhary , Surya Vashisth , Akshay Dudhane , Praful Hambarde , Satya Naryan Tazi , Prashant Patil , Santosh Kumar Vipparthi , Subrahmanyam Murala , Bilel Benjdira , Anas M. Ali , Wadii Boulila , Zahra Moammeri , Ahmad Mahmoudi-Aznaveh , Ali Karbasi , Hossein Motamednia , Liangyan Li , Guanhua Zhao , Kevin Le , Yimo Ning , Haoxuan Huang , Jun Chen

This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world bokeh simulation problem, where the goal was…

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