Point Cloud Compression, Enhancement and Applications: From 3D Perception to Large Models

Point clouds have the strong capability for modeling 3D objects and scenes, which can be widely used in diverse applications and thus generate the burdens of transmission and storage. Efficient compression algorithms have been explored extensively, and research efforts have also been invested to enhancement algorithms. Moreover, the quality of point clouds can influence 3D analysis tasks, e.g., classification, segmentation, detection, and multimodal understanding, etc. Recent 3D multimodal large models can bring better perception optimizations. This tutorial will provide the fundamental knowledge for point cloud compression, enhancement and applications, and place emphasis on the influences of point cloud quality to human and machine perceptions. We will also discuss the progress of international standards and open source projects for point cloud technologies. From this tutorial, audiences are expected to grasp the basic knowledge and recent progress of point cloud technologies, and promote the research developments in both academia and industrial communities.

Authors

Institutions

Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1145/3664647.3689172
Citations
15
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
3.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Point Cloud Compression, Enhancement and Applications: From 3D Perception to Large Models

Ge Li, Wei Gao
15 citations
Advanced Vision and Imaging
3.74
article

Point Cloud Compression, Enhancement and Applications: From 3D Perception to Large Models

Ge Li, Wei Gao
article en
15 citations

Abstract

Point clouds have the strong capability for modeling 3D objects and scenes, which can be widely used in diverse applications and thus generate the burdens of transmission and storage. Efficient compression algorithms have been explored extensively, and research efforts have also been invested to enhancement algorithms. Moreover, the quality of point clouds can influence 3D analysis tasks, e.g., classification, segmentation, detection, and multimodal understanding, etc. Recent 3D multimodal large models can bring better perception optimizations. This tutorial will provide the fundamental knowledge for point cloud compression, enhancement and applications, and place emphasis on the influences of point cloud quality to human and machine perceptions. We will also discuss the progress of international standards and open source projects for point cloud technologies. From this tutorial, audiences are expected to grasp the basic knowledge and recent progress of point cloud technologies, and promote the research developments in both academia and industrial communities.

Peking University (CN), Peng Cheng Laboratory (CN)
Openalex Percentile: Top 5%
Advanced Vision and Imaging
3.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.