7 papers
After a Decade: Bringing Shadow Removal into the Real World with Agentic Training Data
Shilin Hu, Jingyi Xu, Dimitris Samaras +1
Shadow removal looks nearly solved on established benchmarks, yet remains brittle in the real world. Models have advanced; the paired training data they rely on have barely changed…
Domain-Grounded Candidate Selection for Agentic Image Editing: A Shadow Removal Case
Shilin Hu, Jingyi Xu, Dimitris Samaras +1
Commercial vision-language models are reshaping computer vision, with visual priors broad enough to rival task-specific systems. This raises a natural question: do they reduce the…
Cast and Attached Shadow Detection via Iterative Light and Geometry Reasoning
Shilin Hu, Jingyi Xu, Sagnik Das +2
Shadows encode rich information about scene geometry and illumination, yet existing methods either predict a unified shadow mask or overlook attached shadows entirely. We address t…
Embedding Physical Reasoning into Diffusion-Based Shadow Generation Under the Sun and Sky
Shilin Hu, Jingyi Xu, Akshat Dave +2
Generating realistic cast shadows for inserted foreground objects requires reasoning about scene geometry and illumination. However, most learning-based approaches treat shadow gen…
MLI-NeRF: Multi-Light Intrinsic-Aware Neural Radiance Fields
Yixiong Yang, Shilin Hu, Haoyu Wu +3
Current methods for extracting intrinsic image components, such as reflectance and shading, primarily rely on statistical priors. These methods focus mainly on simple synthetic sce…
Shadow Removal Refinement via Material-Consistent Shadow Edges
Shilin Hu, Hieu Le, ShahRukh Athar +2
Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However, shadows do not modify the intrinsic color…
Learning Relighting and Intrinsic Decomposition in Neural Radiance Fields
Yixiong Yang, Shilin Hu, Haoyu Wu +3
The task of extracting intrinsic components, such as reflectance and shading, from neural radiance fields is of growing interest. However, current methods largely focus on syntheti…