Feb. 22, 2024, 5:45 a.m. | Huankang Guan, Ke Xu, Rynson W. H. Lau

cs.CV updates on arXiv.org arxiv.org

arXiv:2402.13631v1 Announce Type: new
Abstract: Shadow detection is a challenging task as it requires a comprehensive understanding of shadow characteristics and global/local illumination conditions. We observe from our experiment that state-of-the-art deep methods tend to have higher error rates in differentiating shadow pixels from non-shadow pixels in dark regions (ie, regions with low-intensity values). Our key insight to this problem is that existing methods typically learn discriminative shadow features from the whole image globally, covering the full range of intensity …

arxiv cs.cv detection robust shadow type

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