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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

This paper presents an overview of NTIRE 2025 the First Challenge on Event-Based Image Deblurring, detailing the proposed methodologies and corresponding results. The primary goal of the challenge is to design an event-based method that…

Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. In this challenge, we present the evaluation results from 3 competition…

Computer Vision and Pattern Recognition · Computer Science 2020-05-12 Seungjun Nah , Sanghyun Son , Radu Timofte , Kyoung Mu Lee

Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews the NTIRE 2021 Challenge on Image Deblurring. In this challenge report, we describe…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Seungjun Nah , Sanghyun Son , Suyoung Lee , Radu Timofte , Kyoung Mu Lee

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 first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper describes the challenge, and focuses on the proposed solutions…

This paper presents a comprehensive review of the NTIRE 2025 Low-Light Image Enhancement (LLIE) Challenge, highlighting the proposed solutions and final outcomes. The objective of the challenge is to identify effective networks capable of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xiaoning Liu , Zongwei Wu , Florin-Alexandru Vasluianu , Hailong Yan , Bin Ren , Yulun Zhang , Shuhang Gu , Le Zhang , Ce Zhu , Radu Timofte , Kangbiao Shi , Yixu Feng , Tao Hu , Yu Cao , Peng Wu , Yijin Liang , Yanning Zhang , Qingsen Yan , Han Zhou , Wei Dong , Yan Min , Mohab Kishawy , Jun Chen , Pengpeng Yu , Anjin Park , Seung-Soo Lee , Young-Joon Park , Zixiao Hu , Junyv Liu , Huilin Zhang , Jun Zhang , Fei Wan , Bingxin Xu , Hongzhe Liu , Cheng Xu , Weiguo Pan , Songyin Dai , Xunpeng Yi , Qinglong Yan , Yibing Zhang , Jiayi Ma , Changhui Hu , Kerui Hu , Donghang Jing , Tiesheng Chen , Zhi Jin , Hongjun Wu , Biao Huang , Haitao Ling , Jiahao Wu , Dandan Zhan , G Gyaneshwar Rao , Vijayalaxmi Ashok Aralikatti , Nikhil Akalwadi , Ramesh Ashok Tabib , Uma Mudenagudi , Ruirui Lin , Guoxi Huang , Nantheera Anantrasirichai , Qirui Yang , Alexandru Brateanu , Ciprian Orhei , Cosmin Ancuti , Daniel Feijoo , Juan C. Benito , Álvaro García , Marcos V. Conde , Yang Qin , Raul Balmez , Anas M. Ali , Bilel Benjdira , Wadii Boulila , Tianyi Mao , Huan Zheng , Yanyan Wei , Shengeng Tang , Dan Guo , Zhao Zhang , Sabari Nathan , K Uma , A Sasithradevi , B Sathya Bama , S. Mohamed Mansoor Roomi , Ao Li , Xiangtao Zhang , Zhe Liu , Yijie Tang , Jialong Tang , Zhicheng Fu , Gong Chen , Joe Nasti , John Nicholson , Zeyu Xiao , Zhuoyuan Li , Ashutosh Kulkarni , Prashant W. Patil , Santosh Kumar Vipparthi , Subrahmanyam Murala , Duan Liu , Weile Li , Hangyuan Lu , Rixian Liu , Tengfeng Wang , Jinxing Liang , Chenxin Yu

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 AIM 2025 (Advances in Image Manipulation) Low-Light RAW Video Denoising Challenge. The task is to develop methods that denoise low-light RAW video by exploiting temporal redundancy while operating under exposure-time…

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,…

Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challenge on video temporal super-resolution (frame interpolation)…

Computer Vision and Pattern Recognition · Computer Science 2020-05-05 Seungjun Nah , Sanghyun Son , Radu Timofte , Kyoung Mu Lee

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 2025 Efficient Burst HDR and Restoration Challenge, which aims to advance efficient multi-frame high dynamic range (HDR) and restoration techniques. The challenge is based on a novel RAW multi-frame fusion…

Blind motion deblurring is one of the most basic and challenging problems in image processing and computer vision. It aims to recover a sharp image from its blurred version knowing nothing about the blur process. Many existing methods use…

Computer Vision and Pattern Recognition · Computer Science 2019-01-09 Quan Yuan , Junxia Li , Lingwei Zhang , Zhefu Wu , Guangyu Liu

Videos in the real-world contain various dynamics and motions that may look unnaturally discontinuous in time when the recordedframe rate is low. This paper reports the second AIM challenge on Video Temporal Super-Resolution (VTSR), a.k.a.…

Computer Vision and Pattern Recognition · Computer Science 2020-09-29 Sanghyun Son , Jaerin Lee , Seungjun Nah , Radu Timofte , Kyoung Mu Lee

This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable of…

This paper presents a comprehensive review of the AIM 2025 Challenge on Inverse Tone Mapping (ITM). The challenge aimed to push forward the development of effective ITM algorithms for HDR image reconstruction from single LDR inputs,…

This paper presents NTIRE 2026, the 3rd Restore Any Image Model (RAIM) challenge on multi-exposure image fusion in dynamic scenes. We introduce a benchmark that targets a practical yet difficult HDR imaging setting, where exposure…

This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demoireing is a difficult task of removing moire patterns from…

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