March 25, 2024, 4:45 a.m. | Qingyang Liu, Junqi You, Jianting Wang, Xinhao Tao, Bo Zhang, Li Niu

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.15234v1 Announce Type: new
Abstract: In the realm of image composition, generating realistic shadow for the inserted foreground remains a formidable challenge. Previous works have developed image-to-image translation models which are trained on paired training data. However, they are struggling to generate shadows with accurate shapes and intensities, hindered by data scarcity and inherent task complexity. In this paper, we resort to foundation model with rich prior knowledge of natural shadow images. Specifically, we first adapt ControlNet to our task …

arxiv cs.cv diffusion diffusion model image shadow type

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