18 citations · 22 across the 7 of their papers we have counts for
7 papers
SuperGaussian: Repurposing Video Models for 3D Super Resolution
Yuan Shen, Duygu Ceylan, Paul Guerrero +4
We present a simple, modular, and generic method that upsamples coarse 3D models by adding geometric and appearance details. While generative 3D models now exist, they do not yet m…
DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan +8
We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model inco…
Controllable Dynamic Appearance for Neural 3D Portraits
ShahRukh Athar, Zhixin Shu, Zexiang Xu +4
Recent advances in Neural Radiance Fields (NeRFs) have made it possible to reconstruct and reanimate dynamic portrait scenes with control over head-pose, facial expressions and vie…
Strivec: Sparse Tri-Vector Radiance Fields
Quankai Gao, Qiangeng Xu, Hao Su +2
We propose Strivec, a novel neural representation that models a 3D scene as a radiance field with sparsely distributed and compactly factorized local tensor feature grids. Our appr…
Neural Free-Viewpoint Relighting for Glossy Indirect Illumination
Nithin Raghavan, Yan Xiao, Kai-En Lin +5
Precomputed Radiance Transfer (PRT) remains an attractive solution for real-time rendering of complex light transport effects such as glossy global illumination. After precomputati…
MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field
Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang +3
We present MovingParts, a NeRF-based method for dynamic scene reconstruction and part discovery. We consider motion as an important cue for identifying parts, that all particles on…