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Point cloud compression (PCC) has made remarkable achievement in recent years. In the mean time, point cloud quality assessment (PCQA) also realize gratifying development. Some recently emerged metrics present robust performance on public point cloud assessment databases. However, these metrics have not been evaluated specifically for PCC to verify whether they exhibit consistent performance with the subjective perception. In this paper, we establish a new dataset for compression evaluation first, which contains 175 compressed point clouds in total, deriving from 7 compression algorithms with 5 compression levels. Then leveraging the proposed dataset, we evaluate the performance of the existing PCQA metrics in terms of different compression types. The results demonstrate some deficiencies of existing metrics in compression evaluation.
We present an efficient voxelization method to encode the geometry and attributes of 3D point clouds obtained from autonomous vehicles. Due to the circular scanning trajectory of sensors, the geometry of LiDAR point clouds is inherently different fro
In video-based dynamic point cloud compression (V-PCC), 3D point clouds are projected onto 2D images for compressing with the existing video codecs. However, the existing video codecs are originally designed for natural visual signals, and it fails t
Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions, which are functions def
In this manuscript we propose two objective terms for neural image compression: a compression objective and a cycle loss. These terms are applied on the encoder output of an autoencoder and are used in combination with reconstruction losses. The comp
The sparse LiDAR point clouds become more and more popular in various applications, e.g., the autonomous driving. However, for this type of data, there exists much under-explored space in the corresponding compression framework proposed by MPEG, i.e.