Auto-Points: Automatic Learning for Point Cloud Analysis With Neural Architecture Search-Reference-Cited by-同舟云学术

Auto-Points: Automatic Learning for Point Cloud Analysis With Neural Architecture Search

Published:2024 Issue: Volume:26 Page:2878-2893
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Wang Li¹^ORCID,Xie Tao²^ORCID,Zhang Xinyu¹^ORCID,Jiang Zhiqiang²^ORCID,Yang Linqi²^ORCID,Zhang Haoming²^ORCID,Li Xiaoyu²^ORCID,Ren Yilong³^ORCID,Yu Haiyang³^ORCID,Li Jun¹^ORCID,Liu Huaping⁴^ORCID

Affiliation:

1. State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China

2. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China

3. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, Beihang University, Beijing, China

4. State Key Laboratory of Intelligent Technology and the Systems Department of Computer Science and Technology, Tsinghua University, Beijing, China

Funder

National High Technology Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

State Key Laboratory of Robotics and Systems

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10223431.pdf?arnumber=10223431

Reference87 articles.

1. SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

2. A novel system for off-line 3D seam extraction and path planning based on point cloud segmentation for arc welding robot

3. Point-cloud based 3D object detection and classification methods for self-driving applications: A survey and taxonomy

4. A Survey of Augmented Reality

5. PointNet: Deep learning on point sets for 3D classification and segmentation;Qi,2017

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1. SMIFormer: Learning Spatial Feature Representation for 3D Object Detection from 4D Imaging Radar via Multi-View Interactive Transformers;Sensors;2023-11-27

2. Point-NAS: A Novel Neural Architecture Search Framework for Point Cloud Analysis;IEEE Transactions on Image Processing;2023