5 papers
SpeedyGS: Content-Aware 3D Gaussian Splatting Compression via Two-Stage Optimization
Junteng Zhang, Tong Chen, Yuxin Zhao +3
Recent progress in compressing large-scale 3D Gaussian Splatting (3DGS) data has substantially reduced storage footprint, network transmission bandwidth, and memory traffic to GPU…
PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression
Jiahao Zhu, Kang You, Dandan Ding +1
LiDAR point cloud compression is vital for autonomous systems to handle massive data from high-resolution sensors. While learned entropy modeling built upon octree structures yield…
Efficient LiDAR Reflectance Compression via Scanning Serialization
Jiahao Zhu, Kang You, Dandan Ding +1
Reflectance attributes in LiDAR point clouds provide essential information for downstream tasks but remain underexplored in neural compression methods. To address this, we introduc…
RENO: Real-Time Neural Compression for 3D LiDAR Point Clouds
Kang You, Tong Chen, Dandan Ding +2
Despite the substantial advancements demonstrated by learning-based neural models in the LiDAR Point Cloud Compression (LPCC) task, realizing real-time compression - an indispensab…
Efficient and Generic Point Model for Lossless Point Cloud Attribute Compression
Kang You, Pan Gao, Zhan Ma
The past several years have witnessed the emergence of learned point cloud compression (PCC) techniques. However, current learning-based lossless point cloud attribute compression…