HIGHLIGHTS
- who: October et al. from the Universitu00e9 Paris-Saclay, France University of Technology Sydney have published the article: LVAC: Learned volumetric attribute compression for point clouds using coordinate based networks, in the Journal: (JOURNAL)
- what: Motivated by this, the authors propose the first end-to-end learned compression framework for volumetric Frontiers in Signal Processing frontiersin.org 10.3389/frsip.2022.1008812 the ith point and yi is a vector of attributes associated with the point. The authors focus on this second step, namely attribute compression conditioned on the decoded geometry, assuming geometry compression (such . . .
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