Enhancing Octree-Based Context Models for Point Cloud Geometry Compression With Attention-Based Child Node Number Prediction-Reference-Cited by-同舟云学术

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Enhancing Octree-Based Context Models for Point Cloud Geometry Compression With Attention-Based Child Node Number Prediction

Published:2024 Issue: Volume:31 Page:1835-1839
ISSN:1070-9908
Container-title:IEEE Signal Processing Letters
language:
Short-container-title:IEEE Signal Process. Lett.

Author:

Sun Chang¹^ORCID,Yuan Hui²^ORCID,Mao Xiaolong¹,Lu Xin³^ORCID,Hamzaoui Raouf⁴^ORCID

Affiliation:

1. Joint SDU-NTU Centre for Artificial Intelligence Research & School of Software, Shandong University, Jinan, China

2. School of Control Science and Engineering, Shandong University, Jinan, China

3. School of Computer Science and Informatics, De Montfort University, Leicester, U.K.

4. School of Engineering and Sustainable Development, De Montfort University, Leicester, U.K.

Funder

National Natural Science Foundation of China

High-end Foreign Experts Recruitment Plan of Chinese Ministry of Science and Technology

Taishan Scholar Project of Shandong Province

Natural Science Foundation of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/97/10380231/10596661.pdf?arnumber=10596661

Reference28 articles.

1. A Sampling-based 3D Point Cloud Compression Algorithm for Immersive Communication

2. Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality

3. Point Cloud Compression with Range Image-Based Entropy Model for Autonomous Driving

4. Set Partitioning in Hierarchical Trees for Point Cloud Attribute Compression

5. 3D Point Cloud Attribute Compression via Graph Prediction

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