Clustering based Point Cloud Representation Learning for 3D Analysis
Author:
Affiliation:
1. ReLER, AAII, University of Technology Sydney
2. ReLER, CCAI, Zhejiang University
3. Xi’an Jiaotong University
Funder
Australian Research Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377956.pdf?arnumber=10377956
Reference116 articles.
1. SEGCloud: Semantic Segmentation of 3D Point Clouds
2. SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud
3. 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
4. VV-Net: Voxel VAE Net With Group Convolutions for Point Cloud Segmentation
5. RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation
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