7 citations · 8 across the 5 of their papers we have counts for
5 papers
WildRelight: A Real-World Benchmark and Physics-Guided Adaptation for Single-Image Relighting
Lezhong Wang, Mehmet Onurcan Kaya, Siavash Bigdeli +1
Recent single-image relighting methods, powered by advanced generative models, have achieved impressive photorealism on synthetic benchmarks. However, their effectiveness in the co…
ReLumix: Extending Image Relighting to Video via Video Diffusion Models
Lezhong Wang, Shutong Jin, Ruiqi Cui +3
Controlling illumination during video post-production is a crucial yet elusive goal in computational photography. Existing methods often lack flexibility, restricting users to cert…
Physically-based Lighting Generation for Robotic Manipulation
Shutong Jin, Lezhong Wang, Ben Temming +1
In this paper, we propose the first framework that leverages physically-based inverse rendering for novel lighting generation on existing real-world human demonstrations of robotic…
Materialist: Physically Based Editing Using Single-Image Inverse Rendering
Lezhong Wang, Duc Minh Tran, Ruiqi Cui +5
Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle t…
StereoDiffusion: Training-Free Stereo Image Generation Using Latent Diffusion Models
Lezhong Wang, Jeppe Revall Frisvad, Mark Bo Jensen +1
The demand for stereo images increases as manufacturers launch more XR devices. To meet this demand, we introduce StereoDiffusion, a method that, unlike traditional inpainting pipe…