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Found 4 papers, 4 papers with code
Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes
Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces.
Efficient and Generic Point Model for Lossless Point Cloud Attribute Compression
In this paper, we propose PoLoPCAC, an efficient and generic lossless PCAC method that achieves high compression efficiency and strong generalizability simultaneously.
IPDAE: Improved Patch-Based Deep Autoencoder for Lossy Point Cloud Geometry Compression
Point cloud is a crucial representation of 3D contents, which has been widely used in many areas such as virtual reality, mixed reality, autonomous driving, etc.
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression
Unlike existing point cloud compression networks, which apply feature extraction and reconstruction on the entire point cloud, we divide the point cloud into patches and compress each patch independently.
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