Point Cloud Compression, Enhancement and Applications: From 3D Perception to Large Models
Authors: 
Wei Gao, Ge LiAuthors Info & Claims
Pages 11292 - 11293
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.
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Index Terms
- Point Cloud Compression, Enhancement and Applications: From 3D Perception to Large Models
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Information
Published In
October 2024
11719 pages
ISBN:9798400706868
DOI:10.1145/3664647
- General Chairs:
- Jianfei Cai,
- Mohan Kankanhalli,
- Balakrishnan Prabhakaran,
- Susanne Boll,
- Program Chairs:
- Ramanathan Subramanian,
- Liang Zheng,
- Vivek K. Singh,
- Pablo Cesar,
- Lexing Xie,
- Dong Xu
Copyright © 2024 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
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Publication History
Published: 28 October 2024
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Funding Sources
- Natural Science Foundation of China
- Guangdong Basic and Applied Basic Research Foundation
- Shenzhen Science and Technology Program
- CAAI-MindSpore Open Fund, developed on OpenI Community
- The Major Key Project of PCL
- Guangdong Province Pearl River Talent Program
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MM '24
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MM '24: The 32nd ACM International Conference on Multimedia
October 28 - November 1, 2024
Melbourne VIC, Australia
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MM '24 Paper Acceptance Rate 1,150 of 4,385 submissions, 26%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%
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