Results 11 to 20 of about 3,061 (275)
Inter-Frame Compression for Dynamic Point Cloud Geometry Coding
IEEE Transactions on Image ProcessingEfficient point cloud compression is essential for applications like virtual and mixed reality, autonomous driving, and cultural heritage. This paper proposes a deep learning-based inter-frame encoding scheme for dynamic point cloud geometry compression.
Anique Akhtar +2 more
exaly +5 more sources
Learned Point Cloud Geometry Compression
CoRR, 2019 This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a.k.a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE). In our approach, PCG is first voxelized, scaled and partitioned into non-overlapped 3D cubes, which is then fed ...
Jianqiang Wang 0006 +5 more
openaire +3 more sources
Survey on Deep Learning-Based Point Cloud Compression
Frontiers in Signal Processing, 2022 Point clouds are becoming essential in key applications with advances in capture technologies leading to large volumes of data. Compression is thus essential for storage and transmission.
Maurice Quach +4 more
doaj +2 more sources
Learning-Based Lossless Compression of 3D Point Cloud Geometry [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 5 pages, accepted paper at ICASSP ...
Nguyen, Dat Thanh +3 more
openaire +4 more sources
Dynamic Point Cloud Compression Based on Projections, Surface Reconstruction and Video Compression
Sensors, 2021 In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been
Emil Dumic +2 more
doaj +2 more sources
Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression [PDF]
2019 IEEE International Conference on Image Processing (ICIP), 2019 Published in ICIP 2019. The source code can be found at https://github.com/mauriceqch/pcc_geo_cnn and the supplementary material can be found at https://www.mauricequach.com ...
Quach, Maurice +2 more
openaire +4 more sources
Learning Neural Volumetric Field for Point Cloud Geometry Compression
2022 Picture Coding Symposium (PCS), 2022 In Proceedings of 2022 Picture Coding Symposium (PCS)
Yueyu Hu, Yao Wang 0001
openaire +3 more sources
The JPEG Pleno Learning-Based Point Cloud Coding Standard: Serving Man and Machine
IEEE AccessEfficient 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.
Andre F. R. Guarda +2 more
doaj +2 more sources
Lightweight super resolution network for point cloud geometry compression
2024 Data Compression Conference (DCC), 2023 This paper presents an approach for compressing point cloud geometry by leveraging a lightweight super-resolution network. The proposed method involves decomposing a point cloud into a base point cloud and the interpolation patterns for reconstructing the original point cloud.
Wei Zhang 0072 +3 more
openaire +3 more sources
Multiscale Point Cloud Geometry Compression [PDF]
2021 Data Compression Conference (DCC), 2021 Recent years have witnessed the growth of point cloud based applications because of its realistic and fine-grained representation of 3D objects and scenes. However, it is a challenging problem to compress sparse, unstructured, and high-precision 3D points for efficient communication.
Jianqiang Wang 0006 +3 more
openaire +2 more sources