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20212025
most citedPointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes

1 citations · 2 across the 8 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.LG2024

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…

cs.CV2024

Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds

Kai Liu, Kang You, Pan Gao

Stable diffusion networks have emerged as a groundbreaking development for their ability to produce realistic and detailed visual content. This characteristic renders them ideal de…

cs.CV2024

Global Attention-Guided Dual-Domain Point Cloud Feature Learning for Classification and Segmentation

Zihao Li, Pan Gao, Kang You +2

Previous studies have demonstrated the effectiveness of point-based neural models on the point cloud analysis task. However, there remains a crucial issue on producing the efficien…

cs.CV2024★ 1 cited

Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes

Kang You, Kai Liu, Li Yu +2

Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces…

cs.CV2024

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…