From the 1 of 5 linked papers with an AI index.
5 papers
WildShadowRemover: In-the-Wild Video Shadow Removal via Detail-Preserving Video Diffusion Models
Jiamin Xu, Cong Wang, Zheng Dong +4
The paper introduces WildShadowRemover, a system that fine‑tunes a pretrained video diffusion model to remove shadows from real‑world videos while preserving fine details and tempo…
TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
Zheng Dong, Daifei Qiu, Pinxuan Dai +5
Consumer-level applications require fast optimization of 3D Gaussian Splatting (3DGS) with high-fidelity novel view rendering. However, existing 3DGS acceleration approaches still…
HetScene: Heterogeneity-Aware Diffusion for Dense Indoor Scene Generation
Zini Chen, Junming Huang, Rong Zhang +4
Generating controllable and physically plausible indoor scenes is a pivotal prerequisite for constructing high-fidelity simulation environments for embodied AI. However, existing d…
OmniSR: Shadow Removal under Direct and Indirect Lighting
Jiamin Xu, Zelong Li, Yuxin Zheng +4
Shadows can originate from occlusions in both direct and indirect illumination. Although most current shadow removal research focuses on shadows caused by direct illumination, shad…
Detail-Preserving Latent Diffusion for Stable Shadow Removal
Jiamin Xu, Yuxin Zheng, Zelong Li +4
Achieving high-quality shadow removal with strong generalizability is challenging in scenes with complex global illumination. Due to the limited diversity in shadow removal dataset…