CVJun 18, 2025

NTIRE 2025 Image Shadow Removal Challenge Report

arXiv:2506.15524v122 citationsh-index: 982025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Originality Synthesis-oriented
AI Analysis

It addresses the problem of removing shadows from images for computer vision applications, but is incremental as it follows previous challenge editions.

This paper reports on the NTIRE 2025 Image Shadow Removal Challenge, where 306 participants registered and 17 teams submitted solutions evaluated on reconstruction fidelity and visual perception using the WSRD+ dataset.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes