Unified 3D and 4D Panoptic Segmentation via Dynamic Shifting Networks
Author:
Affiliation:
1. S-Lab, Nanyang Technological University, Singapore
2. School of Computing, National University of Singapore, Singapore
3. SenseTime Research, China
4. Chinese University of Hong Kong, Central Ave, Hong Kong
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/34/10490207/10380457.pdf?arnumber=10380457
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1. PointPillars: Fast Encoders for Object Detection From Point Clouds
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3. SECOND: Sparsely Embedded Convolutional Detection
4. RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation
5. SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud
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