81 citations · 99 across the 5 of their papers we have counts for
6 papers
SACHA: Semantic-Aware Compression for 3D Gaussian Head Avatars
Zihan Zhang, Shanzhi Yin, Xinju Wu +5
Animatable 3D Gaussian head avatars offer high-fidelity and flexible facial rendering, but typically require substantial storage and transmission costs for numerous Gaussian primit…
Towards Efficient 3D Gaussian Human Avatar Compression: A Prior-Guided Framework
Shanzhi Yin, Bolin Chen, Xinju Wu +4
This paper proposes an efficient 3D avatar coding framework that leverages compact human priors and canonical-to-target transformation to enable high-quality 3D human avatar video…
CompGS++: Compressed Gaussian Splatting for Static and Dynamic Scene Representation
Xiangrui Liu, Xinju Wu, Shiqi Wang +2
Gaussian splatting demonstrates proficiency for 3D scene modeling but suffers from substantial data volume due to inherent primitive redundancy. To enable future photorealistic 3D…
CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting
Xiangrui Liu, Xinju Wu, Pingping Zhang +3
Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation. However, the substantial data vo…
Geometric Prior Based Deep Human Point Cloud Geometry Compression
Xinju Wu, Pingping Zhang, Meng Wang +3
The emergence of digital avatars has raised an exponential increase in the demand for human point clouds with realistic and intricate details. The compression of such data becomes…
Subjective Quality Database and Objective Study of Compressed Point Clouds With 6DoF Head-Mounted Display
Xinju Wu, Yun Zhang, Chunling Fan +2
In this paper, we focus on subjective and objective Point Cloud Quality Assessment (PCQA) in an immersive environment and study the effect of geometry and texture attributes in com…