7 papers
HybridINR-PCGC: Hybrid Lossless Point Cloud Geometry Compression Bridging Pretrained Model and Implicit Neural Representation
Wenjie Huang, Qi Yang, Shuting Xia +3
Learning-based point cloud compression presents superior performance to handcrafted codecs. However, pretrained-based methods, which are based on end-to-end training and expected t…
Progressively Deformable 2D Gaussian Splatting for Video Representation at Arbitrary Resolutions
Mufan Liu, Qi Yang, Miaoran Zhao +4
Implicit neural representations (INRs) enable fast video compression and effective video processing, but a single model rarely offers scalable decoding across rates and resolutions…
TVMC: Time-Varying Mesh Compression via Multi-Stage Anchor Mesh Generation
He Huang, Qi Yang, Yiling Xu +2
Time-varying meshes, characterized by dynamic connectivity and varying vertex counts, hold significant promise for applications such as augmented reality. However, their practical…
Light4GS: Lightweight Compact 4D Gaussian Splatting Generation via Context Model
Mufan Liu, Qi Yang, He Huang +4
3D Gaussian Splatting (3DGS) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates tempor…
Point Cloud Compression and Objective Quality Assessment: A Survey
Yiling Xu, Yujie Zhang, Shuting Xia +6
The rapid growth of 3D point cloud data, driven by applications in autonomous driving, robotics, and immersive environments, has led to criticals demand for efficient compression a…
ADC-GS: Anchor-Driven Deformable and Compressed Gaussian Splatting for Dynamic Scene Reconstruction
He Huang, Qi Yang, Mufan Liu +2
Existing 4D Gaussian Splatting methods rely on per-Gaussian deformation from a canonical space to target frames, which overlooks redundancy among adjacent Gaussian primitives and r…