1 citations · 1 across the 7 of their papers we have counts for
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ContraGS: Codebook-Condensed and Trainable Gaussian Splatting for Fast, Memory-Efficient Reconstruction
Sankeerth Durvasula, Sharanshangar Muhunthan, Zain Moustafa +7
3D Gaussian Splatting (3DGS) is a state-of-art technique to model real-world scenes with high quality and real-time rendering. Typically, a higher quality representation can be ach…
LuxDiT: Lighting Estimation with Video Diffusion Transformer
Ruofan Liang, Kai He, Zan Gojcic +4
Estimating scene lighting from a single image or video remains a longstanding challenge in computer vision and graphics. Learning-based approaches are constrained by the scarcity o…
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…
Controllable Weather Synthesis and Removal with Video Diffusion Models
Chih-Hao Lin, Zian Wang, Ruofan Liang +4
Generating realistic and controllable weather effects in videos is valuable for many applications. Physics-based weather simulation requires precise reconstructions that are hard t…