Variable Rate Compression for Raw 3D Point Clouds

In this paper, we propose a novel variable rate deep compression architecture that operates on raw 3D point cloud data. The majority of learning-based point cloud compression methods work on a downsampled representation of the data. Moreover, many existing techniques require training multiple networ...

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Vydané v:	2022 International Conference on Robotics and Automation (ICRA) s. 8748 - 8755
Hlavní autori:	Al Muzaddid, Md Ahmed, Beksi, William J.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 23.05.2022
Predmet:	Automation Big Data in Robotics and Automation Bit rate Computational modeling Deep Learning for Visual Perception Point cloud compression RGB-D Perception Three-dimensional displays Training Visualization
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