Guest Editorial: Deep Learning-based Point Cloud Processing, Compression
and Analysis
- Yun Zhang,
- Raouf Hamzaoui(GE),
- Xu Wang,
- Junhui Hou,
- Giuseppe Valenzise(GE)
Yun Zhang
Sun Yat-Sen University
Corresponding Author:zhangyun2@mail.sysu.edu.cn
Author ProfileAbstract
Point cloud data is a large collection of high dimensional 3D points
with 3D coordinates and attributes, which has been one of the mainstream
representations for emerging 3D applications, such as virtual reality,
autonomous vehicles and robotics. Due to the large-scale unstructured
high-dimensional nature of point clouds, point cloud processing,
transmitting and analysing has been challenging issues in multimedia
signal processing and communication. Deep learning is a powerful tool to
learn statistical knowledge from massive data. Advances in artificial
intelligence, especially deep learning models are offering new
opportunities for point cloud processing, compression and analysis. This
special issue aims at promoting cutting-edge research on deep
learning-based point cloud processing, including object detection,
segmentation, registration, compression, and visual quality assessment.Submitted to Electronics Letters 15 Jun 2024Submitted to Electronics Letters 19 Jun 2024Submission Checks Completed
19 Jun 2024Assigned to Editor
19 Jun 2024Review(s) Completed, Editorial Evaluation Pending
19 Jun 2024Editorial Decision: Accept