5 papers · 1 filter
SURE: Semi-dense Uncertainty-REfined Feature Matching
Sicheng Li, Zaiwang Gu, Jie Zhang +3
Establishing reliable image correspondences is essential for many robotic vision problems. However, existing methods often struggle in challenging scenarios with large viewpoint ch…
GSCodec Studio: A Modular Framework for Gaussian Splat Compression
Sicheng Li, Chengzhen Wu, Hao Li +3
3D Gaussian Splatting and its extension to 4D dynamic scenes enable photorealistic, real-time rendering from real-world captures, positioning Gaussian Splats (GS) as a promising fo…
GIFStream: 4D Gaussian-based Immersive Video with Feature Stream
Hao Li, Sicheng Li, Xiang Gao +3
Immersive video offers a 6-Dof-free viewing experience, potentially playing a key role in future video technology. Recently, 4D Gaussian Splatting has gained attention as an effect…
NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation
Sicheng Li, Hao Li, Yiyi Liao +1
The emergence of Neural Radiance Fields (NeRF) has greatly impacted 3D scene modeling and novel-view synthesis. As a kind of visual media for 3D scene representation, compression w…
DORec: Decomposed Object Reconstruction and Segmentation Utilizing 2D Self-Supervised Features
Jun Wu, Sicheng Li, Sihui Ji +4
Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decompo…