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Found 7 papers, 0 papers with code
Point Cloud Geometry Scalable Coding Using a Resolution and Quality-conditioned Latents Probability Estimator
Experimental results obtained by integrating SRQH in the emerging JPEG Pleno learning-based PC coding standard show that SRQH allows decoding the PC at different qualities and resolutions with a single bitstream while incurring only in a limited RD penalty and increment in complexity w. r. t.
Deep Learning-based Event Data Coding: A Joint Spatiotemporal and Polarity Solution
This paper proposes a novel lossy Deep Learning-based Joint Event data Coding (DL-JEC) solution adopting a single-point cloud representation, thus enabling to exploit the correlation between the spatiotemporal and polarity event information.
The JPEG Pleno Learning-based Point Cloud Coding Standard: Serving Man and Machine
Efficient point cloud coding has become increasingly critical for multiple applications such as virtual reality, autonomous driving, and digital twin systems, where rich and interactive 3D data representations may functionally make the difference.
A Double Deep Learning-based Solution for Efficient Event Data Coding and Classification
This paper proposes a novel double deep learning-based architecture for both event data coding and classification, using a point cloud-based representation for events.
Point Cloud Geometry Scalable Coding with a Quality-Conditioned Latents Probability Estimator
The widespread usage of point clouds (PC) for immersive visual applications has resulted in the use of very heterogeneous receiving conditions and devices, notably in terms of network, hardware, and display capabilities.
Deep Learning-based Compressed Domain Multimedia for Man and Machine: A Taxonomy and Application to Point Cloud Classification
The potential of the proposed taxonomy is demonstrated for the specific case of point cloud classification by designing novel compressed domain processors using the JPEG Pleno Point Cloud Coding standard under development and adaptations of the PointGrid classifier.
IT/IST/IPLeiria Response to the Call for Proposals on JPEG Pleno Point Cloud Coding
This document describes a deep learning-based point cloud geometry codec and a deep learning-based point cloud joint geometry and colour codec, submitted to the Call for Proposals on JPEG Pleno Point Cloud Coding issued in January 2022.
