14 citations · 22 across the 5 of their papers we have counts for
6 papers
Mastering Regional 3DGS: Locating, Initializing, and Editing with Diverse 2D Priors
Lanqing Guo, Yufei Wang, Hezhen Hu +4
Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussia…
SoftShadow: Leveraging Soft Masks for Penumbra-Aware Shadow Removal
Xinrui Wang, Lanqing Guo, Xiyu Wang +2
Recent advancements in deep learning have yielded promising results for the image shadow removal task. However, most existing methods rely on binary pre-generated shadow masks. The…
Single-Image Shadow Removal Using Deep Learning: A Comprehensive Survey
Laniqng Guo, Chong Wang, Yufei Wang +5
Shadow removal aims at restoring the image content within shadow regions, pursuing a uniform distribution of illumination that is consistent between shadow and non-shadow regions.…
Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation
Lanqing Guo, Yingqing He, Haoxin Chen +9
Diffusion models have proven to be highly effective in image and video generation; however, they encounter challenges in the correct composition of objects when generating images o…
ShadowFormer: Global Context Helps Image Shadow Removal
Lanqing Guo, Siyu Huang, Ding Liu +2
Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow…
ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal
Lanqing Guo, Chong Wang, Wenhan Yang +4
Recent deep learning methods have achieved promising results in image shadow removal. However, their restored images still suffer from unsatisfactory boundary artifacts, due to the…