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3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods
Feb. 20, 2024, 5:47 a.m. | Till Beemelmanns, Yuchen Tao, Bastian Lampe, Lennart Reiher, Raphael van Kempen, Timo Woopen, Lutz Eckstein
cs.CV updates on arXiv.org arxiv.org
Abstract: Storing and transmitting LiDAR point cloud data is essential for many AV applications, such as training data collection, remote control, cloud services or SLAM. However, due to the sparsity and unordered structure of the data, it is difficult to compress point cloud data to a low volume. Transforming the raw point cloud data into a dense 2D matrix structure is a promising way for applying compression algorithms. We propose a new lossless and calibrated 3D-to-2D …
arxiv cloud compression cs.ai cs.cv eess.iv image network neural network recurrent neural network type
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