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20232026
most citedLatent Feature-Guided Diffusion Models for Shadow Removal

3 citations · 4 across the 8 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

MetaShadow: Object-Centered Shadow Detection, Removal, and Synthesis

Tianyu Wang, Jianming Zhang, Haitian Zheng +7

Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one…

cs.CV2024

Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment

Yizhi Song, Liu He, Zhifei Zhang +8

Personalized image generation has emerged from the recent advancements in generative models. However, these generated personalized images often suffer from localized artifacts such…

cs.CV2024

Generative Image Layer Decomposition with Visual Effects

Jinrui Yang, Qing Liu, Yijun Li +7

Recent advancements in large generative models, particularly diffusion-based methods, have significantly enhanced the capabilities of image editing. However, achieving precise cont…

cs.CV2024★ 1 cited

Thinking Outside the BBox: Unconstrained Generative Object Compositing

Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang +6

Compositing an object into an image involves multiple non-trivial sub-tasks such as object placement and scaling, color/lighting harmonization, viewpoint/geometry adjustment, and s…

cs.CV2024

IMPRINT: Generative Object Compositing by Learning Identity-Preserving Representation

Yizhi Song, Zhifei Zhang, Zhe Lin +7

Generative object compositing emerges as a promising new avenue for compositional image editing. However, the requirement of object identity preservation poses a significant challe…