From the 1 of 4 linked papers with an AI index.
4 papers
Efficient LiDAR Reflectance Compression via Scanning Serialization
Jiahao Zhu, Kang You, Dandan Ding +1
The paper introduces SerLiC, a neural compression framework that serializes LiDAR point clouds into 1D scan-order sequences and uses a Mamba-based model to efficiently compress ref…
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…
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…
Att2CPC: Attention-Guided Lossy Attribute Compression of Point Clouds
Kai Liu, Kang You, Pan Gao +1
With the great progress of 3D sensing and acquisition technology, the volume of point cloud data has grown dramatically, which urges the development of efficient point cloud compre…