NTIRE 2025 Image Shadow Removal Challenge Report

• URL: http://arxiv.org/abs/2506.15524v1
• Date: Wed, 18 Jun 2025 14:58:49 GMT
• Title: NTIRE 2025 Image Shadow Removal Challenge Report
• Authors: Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou, Cailian Chen, Zongwei Wu, Radu Timofte, Mingjia Li, Jin Hu, Hainuo Wang, Hengxing Liu, Jiarui Wang, Qiming Hu, Xiaojie Guo, Xin Lu, Jiarong Yang, Yuanfei Bao, Anya Hu, Zihao Fan, Kunyu Wang, Jie Xiao, Xi Wang, Xueyang Fu, Zheng-Jun Zha, Yu-Fan Lin, Chia-Ming Lee, Chih-Chung Hsu, Xingbo Wang, Dong Li, Yuxu Chen, Bin Chen, Yuanbo Zhou, Yuanbin Chen, Hongwei Wang, Jiannan Lin, Qinquan Gao, Tong Tong, Zhao Zhang, Yanyan Wei, Wei Dong, Han Zhou, Seyed Amirreza Mousavi, Jun Chen, Haobo Liang, Jiajie Jing, Junyu Li, Yan Yang, Seoyeon Lee, Chaewon Kim, Ziyu Feng, Shidi Chen, Bowen Luan, Zewen Chen, Vijayalaxmi Ashok Aralikatti, G Gyaneshwar Rao, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Anas M. Ali, Bilel Benjdira, Wadii Boulila, Alexandru Brateanu, Cosmin Ancuti, Tanmay Chaturvedi, Manish Kumar, Anmol Srivastav, Daksh Trivedi, Shashwat Thakur, Kishor Upla, Zeyu Xiao, Zhuoyuan Li, Boda Zhou, Shashank Shekhar, Kele Xu, Qisheng Xu, Zijian Gao, Tianjiao Wan, Suiyi Zhao, Bo Wang, Yan Luo, Mingshen Wang, Yilin Zhang,
• Abstract summary: This work examines the findings of the NTIRE 2025 Shadow Removal Challenge.<n>A total of 306 participants have registered, with 17 teams successfully submitting their solutions.<n>The challenge had two evaluation tracks: one focusing on reconstruction fidelity and the other on visual perception through a user study.
• Score: 125.80015208285496
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions during the final evaluation phase. Following the last two editions, this challenge had two evaluation tracks: one focusing on reconstruction fidelity and the other on visual perception through a user study. Both tracks were evaluated with images from the WSRD+ dataset, simulating interactions between self- and cast-shadows with a large number of diverse objects, textures, and materials.

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