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 dataset, comprising nine noisy and misaligned RAW frames with various exposure levels per scene. Participants were tasked with developing solutions capable of effectively fusing these frames while adhering to strict efficiency constraints: fewer than 30 million model parameters and a computational budget under 4.0 trillion FLOPs. A total of 217 participants registered, with six teams finally submitting valid solutions. The top-performing approach achieved a PSNR of 43.22 dB, showcasing the potential of novel methods in this domain. This paper provides a comprehensive overview of the challenge, compares the proposed solutions, and serves as a valuable reference for researchers and practitioners in efficient burst HDR and restoration.
View on arXiv@article{lee2025_2505.12089,
title={ NTIRE 2025 Challenge on Efficient Burst HDR and Restoration: Datasets, Methods, and Results },
author={ Sangmin Lee and Eunpil Park and Angel Canelo and Hyunhee Park and Youngjo Kim and Hyung-Ju Chun and Xin Jin and Chongyi Li and Chun-Le Guo and Radu Timofte and Qi Wu and Tianheng Qiu and Yuchun Dong and Shenglin Ding and Guanghua Pan and Weiyu Zhou and Tao Hu and Yixu Feng and Duwei Dai and Yu Cao and Peng Wu and Wei Dong and Yanning Zhang and Qingsen Yan and Simon J. Larsen and Ruixuan Jiang and Senyan Xu and Xingbo Wang and Xin Lu and Marcos V. Conde and Javier Abad-Hernandez and Alvaro Garcıa-Lara and Daniel Feijoo and Alvaro Garcıa and Zeyu Xiao and Zhuoyuan Li },
journal={arXiv preprint arXiv:2505.12089},
year={ 2025 }
}