Improved Multi-Scale Grid Rendering of Point Clouds for Radar Object Detection Networks-Reference-Cited by-同舟云学术

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Improved Multi-Scale Grid Rendering of Point Clouds for Radar Object Detection Networks

Published:2023-06-28 Issue: Volume: Page:
ISSN:
Container-title:2023 26th International Conference on Information Fusion (FUSION)
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Author:

Köhler Daniel¹,Quach Maurice²,Ulrich Michael²,Meinl Frank¹,Bischoff Bastian²,Blume Holger³

Affiliation:

1. Robert Bosch GmbH, Cross-Domain Computing Solutions,Germany

2. Robert Bosch GmbH, Corporate Research,Germany

3. Leibniz University Hannover, Institute of Microelectronic Systems,Germany

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10223725/10224076/10224223.pdf?arnumber=10224223

Reference41 articles.

1. Scale-Aware Attention-Based PillarsNet (SAPN) Based 3D Object Detection for Point Cloud

2. Deep learning based 3d object detection for automotive radar and camera;meyer;2019 16th European Radar Conference (EuRAD) EuRAD,0

3. HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection

4. You Only Look Once: Unified, Real-Time Object Detection

5. nuScenes: A Multimodal Dataset for Autonomous Driving

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning-Driven State Correction: A Hybrid Architecture for Radar-Based Dynamic Occupancy Grid Mapping;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

2. ClusterFusion: Leveraging Radar Spatial Features for Radar-Camera 3D Object Detection in Autonomous Vehicles;IEEE Access;2023

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