980 citations · 1.1k across the 15 of their papers we have counts for
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UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Kai He, Ruofan Liang, Jacob Munkberg +7
We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-t…
VideoMat: Extracting PBR Materials from Video Diffusion Models
Jacob Munkberg, Zian Wang, Ruofan Liang +2
We leverage finetuned video diffusion models, intrinsic decomposition of videos, and physically-based differentiable rendering to generate high quality materials for 3D models give…
Generative Detail Enhancement for Physically Based Materials
Saeed Hadadan, Benedikt Bitterli, Tizian Zeltner +6
We present a tool for enhancing the detail of physically based materials using an off-the-shelf diffusion model and inverse rendering. Our goal is to enhance the visual fidelity of…
DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models
Ruofan Liang, Zan Gojcic, Huan Ling +8
Understanding and modeling lighting effects are fundamental tasks in computer vision and graphics. Classic physically-based rendering (PBR) accurately simulates the light transport…