4 papers
Towards Practical Lossless Neural Compression for LiDAR Point Clouds
Pengpeng Yu, Haoran Li, Runqing Jiang +4
LiDAR point clouds are fundamental to various applications, yet the extreme sparsity of high-precision geometric details hinders efficient context modeling, thereby limiting the co…
CodecSplat: Ultra-Compact Latent Coding for Feed-Forward 3D Gaussian Splatting
Pengpeng Yu, Runqing Jiang, Qi Zhang +3
While feed-forward 3D Gaussian splatting reconstructs renderable Gaussian primitives from sparse context views without per-scene optimization, existing pipelines do not provide a c…
D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
Wenjie Zheng, Haoji Hu, Jiali Lu +2
Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing studies mainly focus on image clas…
Re-Densification Meets Cross-Scale Propagation: Real-Time Neural Compression of LiDAR Point Clouds
Pengpeng Yu, Haoran Li, Runqing Jiang +3
LiDAR point clouds are fundamental to various applications, yet high-precision scans incur substantial storage and transmission overhead. Existing methods typically convert unorder…