5 citations · 5 across the 4 of their papers we have counts for
4 papers
CRUISE: Cooperative Reconstruction and Editing in V2X Scenarios using Gaussian Splatting
Haoran Xu, Saining Zhang, Peishuo Li +15
Vehicle-to-everything (V2X) communication plays a crucial role in autonomous driving, enabling cooperation between vehicles and infrastructure. While simulation has significantly c…
PUGS: Zero-shot Physical Understanding with Gaussian Splatting
Yinghao Shuai, Ran Yu, Yuantao Chen +9
Current robotic systems can understand the categories and poses of objects well. But understanding physical properties like mass, friction, and hardness, in the wild, remains chall…
RGM: Reconstructing High-fidelity 3D Car Assets with Relightable 3D-GS Generative Model from a Single Image
Xiaoxue Chen, Jv Zheng, Hao Huang +8
The generation of high-quality 3D car assets is essential for various applications, including video games, autonomous driving, and virtual reality. Current 3D generation methods ut…
SA-GS: Scale-Adaptive Gaussian Splatting for Training-Free Anti-Aliasing
Xiaowei Song, Jv Zheng, Shiran Yuan +5
In this paper, we present a Scale-adaptive method for Anti-aliasing Gaussian Splatting (SA-GS). While the state-of-the-art method Mip-Splatting needs modifying the training procedu…