Related references
Note: Only part of the references are listed.Deep Learning for 3D Point Clouds: A Survey
Yulan Guo et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)
LEARNING CONVOLUTIONAL TRANSFORMS FOR LOSSY POINT CLOUD GEOMETRY COMPRESSION
Maurice Quach et al.
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (2019)
3D Point Cloud Geometry Compression on Deep Learning
Tianxin Huang et al.
PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA (MM'19) (2019)
Point Cloud Compression for 3D LiDAR Sensor using Recurrent Neural Network with Residual Blocks
Chenxi Tu et al.
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) (2019)
A Novel Point Cloud Compression Algorithm Based on Clustering
Xuebin Sun et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2019)
Design, Implementation, and Evaluation of a Point Cloud Codec for Tele-Immersive Video
Rufael Mekuria et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2017)
O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
Peng-Shuai Wang et al.
ACM TRANSACTIONS ON GRAPHICS (2017)
OctoMap: an efficient probabilistic 3D mapping framework based on octrees
Armin Hornung et al.
AUTONOMOUS ROBOTS (2013)
One billion points in the cloud - an octree for efficient processing of 3D laser scans
Jan Elseberg et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2013)
Efficient RANSAC for point-cloud shape detection
R. Schnabel et al.
COMPUTER GRAPHICS FORUM (2007)