AI RESEARCH
Towards Practical Lossless Neural Compression for LiDAR Point Clouds
arXiv CS.CV
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ArXi:2603.25260v1 Announce Type: new LiDAR point clouds are fundamental to various applications, yet the extreme sparsity of high-precision geometric details hinders efficient context modeling, thereby limiting the compression speed and performance of existing methods. To address this challenge, we propose a compact representation for efficient predictive lossless coding. Our framework comprises two lightweight modules.