NSAW: An Efficient and Accurate Transformer for Vehicle LiDAR Object Detection
Author:
Affiliation:
1. MOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China
2. HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou, China
Funder
National Nature Science Foundation of China
Zhejiang Provincial Key Research Development Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10262038.pdf?arnumber=10262038
Reference54 articles.
1. RangeDet: In Defense of Range View for LiDAR-based 3D Object Detection
2. SECOND: Sparsely Embedded Convolutional Detection
3. Multi-scale context aggregation by dilated convolutions;yu;arXiv 1511 07122,2015
4. AFDet: Anchor free one stage 3D object detection;ge;arXiv 2006 12671,2020
5. 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-view Spatial Feature Fusion for 3D Object Detection
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1. Recent Advances in 3D Object Detection for Self-Driving Vehicles: A Survey;AI;2024-07-25
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