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NTIRE 2024 Image Shadow Removal Challenge Report

Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou, Zongwei Wu, Cailian Chen, Radu Timofte, Wei Dong, Han Zhou, Yuqiong Tian, Jun Chen, Xueyang Fu, Xin Lü, Yurui Zhu, Xi Wang, Dong Li, Jie Xiao, Yunpeng Zhang, Zheng-Jun Zha, Zhao Zhang, Suiyi Zhao, Bo Wang, Yan Luo, Yanyan Wei, Zhihao Zhao, Long Sun, Tingting Yang, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Bilel Benjdira, Mohammed Nassif, Anis Koubâa, Ahmed Elhayek, Anas M. Ali, Kyotaro Tokoro, Kento Kawai, Kaname Yokoyama, Takuya Seno, Yuki Kondo, Norimichi Ukita, Chenghua Li, Bo Yang, Zhiqi Wu, Chen Gao, Yihan Yu, Sixiang Chen, Kai Zhang, Tian Ye, Wenbin Zou, Yunlong Lin, Zhaohu Xing, Jinbin Bai, Wenhao Chai, Lei Zhu, R Maheshwari, Rakshank Verma, Rahul Tekchandani, Praful Hambarde, Satya Narayan Tazi, Santosh Kumar Vipparthi, Subrahmanyam Murala, Jae-Ho Lee, Seong‐Wan Kim, S M A Sharif, Nodirkhuja Khujaev, Roman Tsoy, Fan Gao, Weidan Yan, Wenze Shao, Dengyin Zhang, Bin Chen, Siqi Zhang, Yanxin Qian, Yuanbin Chen, Yuanbo Zhou, Tong Tong, Rongfeng Wei, Ruiqi Sun, Yue Liu, Nikhil Akalwadi, Amogh Joshi, Sampada Malagi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Ali Murtaza, Uswah Khairuddin, Ahmad Athif Mohd Faudzi, Adinath Dukre, Vivek Deshmukh, Shruti S. Phutke, Ashutosh Kulkarni, Santosh Kumar Vipparthi, Anil Balaji Gonde, Subrahmanyam Murala, Arun karthik K, N Manasa, Shri Hari Priya, Wei Hao, Xingzhuo Yan

202429 citationsDOI

Abstract

This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building on the last year edition, the current challenge was organized in two tracks, with a track focused on increased fidelity reconstruction, and a separate ranking for high performing perceptual quality solutions. Track 1 (fidelity) had 214 registered participants, with 17 teams submitting in the final phase, while Track 2 (perceptual) registered 185 participants, resulting in 18 final phase submissions. Both tracks were based on data from the WSRD dataset, simulating interactions between self-shadows and cast shadows, with a large variety of represented objects, textures, and materials. Improved image alignment enabled increased fidelity reconstruction, with restored frames mostly indistinguishable from the references images for top performing solutions.

Topics & Concepts

Shadow (psychology)Computer scienceComputer visionImage (mathematics)Artificial intelligenceComputer graphics (images)PsychologyPsychotherapistAdvanced Optical Sensing TechnologiesAdvanced X-ray and CT ImagingDigital Radiography and Breast Imaging
NTIRE 2024 Image Shadow Removal Challenge Report | Litcius