Transform Decomposition Switching for Efficient Attribute Compression of 3D Point Clouds Using Neural Networks
Author:
Affiliation:
1. University of Alabama in Huntsville,Department of Electrical & Computer Engineering,AL,USA,35899
2. McLeod Software Corporation,Birmingham,AL,USA,35242
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10216364/10216365/10216537.pdf?arnumber=10216537
Reference24 articles.
1. Deep-PCAC: An End-to-End Deep Lossy Compression Framework for Point Cloud Attributes
2. Microsoft Voxelized Upper Bodies - A Voxelized Point Cloud Dataset;loop;ISO/IEC JTC1/SC29 Joint WG 11/WG1 (MPEG/JPEG) input document m38673/M72012,2016
3. Point Cloud Compression for 3D LiDAR Sensor using Recurrent Neural Network with Residual Blocks
4. G-PCC CE13.18 report on upsampled transform domain prediction in RAHT;flynn;ISO/IEC JCTC1/SC29/WG11 MPEG/m49380,2019
5. A Hybrid Compression Framework for Color Attributes of Static 3D Point Clouds
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