PointMotionNet: Point-Wise Motion Learning for Large-Scale LiDAR Point Clouds Sequences
Author:
Affiliation:
1. University of Maryland
2. Virginia Tech
3. Mitsubishi Electric Research Labs (MERL)
4. Shanghai Jiao Tong University
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9856930/9856648/09856954.pdf?arnumber=9856954
Reference39 articles.
1. Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception
2. PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation
3. SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud
4. InfoFocus: 3D Object Detection for Autonomous Driving with Dynamic Information Modeling
5. KPConv: Flexible and Deformable Convolution for Point Clouds
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