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  4. Temporal Conditional Coding for Dynamic Point Cloud Geometry Compression
 
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Temporal Conditional Coding for Dynamic Point Cloud Geometry Compression

Huang, Bowen  
•
Lazzarotto, Davi
•
Ebrahimi, Touradj  
March 18, 2024
ICASSP 2024 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Point clouds allow for the representation of 3D multimedia content as a set of disconnected points in space. Their inher- ent irregular geometric nature poses a challenge to efficient compression, a critical operation for both storage and trans- mission. This paper proposes a VAE-inspired codec tailored for dynamic point cloud geometry compression, taking ad- vantage of a temporal autoregressive hyperprior to enhance compression performance. Specifically, features derived from adjacent point cloud frames help build a hyperprior for con- ditional entropy coding. Sparse convolutions are leveraged to reach higher computational efficiency when compared to 3D dense convolutions. Remarkably, the proposed approach achieves an average 60.2% BD-rate gain against the contem- porary V-PCC compression standard from MPEG.

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ICASSP2024.pdf

Type

Postprint

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openaccess

License Condition

CC BY

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294.72 KB

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Adobe PDF

Checksum (MD5)

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