Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features-Reference-Cited by-同舟云学术

Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features

Published:2021-11-26 Issue: Volume: Page:
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Container-title:2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
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Author:

Zhang Kuangen,Hao Ming,Wang Jing,Chen Xinxing,Leng Yuquan,de Silva Clarence W.,Fu Chenglong

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9664973/9664984/09665104.pdf?arnumber=9665104

Reference20 articles.

1. VoxNet: A 3D Convolutional Neural Network for real-time object recognition

2. Binary Volumetric Convolutional Neural Networks for 3-D Object Recognition

3. Pointnet: deep learning on point sets for 3D classification and segmentation;qi;2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017

4. Directional pointnet: 3D environmental classification for wearable robotics;zhang,2019

5. Dynamic graph cnn for learning on point clouds;wang,2018

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