Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection
Author:
Affiliation:
1. Chinese Academy of Sciences,Institute of Automation
2. Hunan University
3. TuSimple
4. Centre for Artificial Intelligence and Robotics (HKISI_CAS)
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10376534.pdf?arnumber=10376534
Reference51 articles.
1. A method for registration of 3-D shapes
2. Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection;Bewley,2020
3. Annotating Object Instances with a Polygon-RNN
4. MPPNet: Multi-frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection
5. VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking
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2. SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03
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