6DoF-3D: Efficient and accurate 3D object detection using six degrees-of-freedom for autonomous driving

Author:

Li ZhenORCID,Yang Zijun,Gao Yuliang,Du Yuren,Serikawa Seiichi,Zhang LifengORCID

Funder

Japan Science and Technology Agency

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference63 articles.

1. Robust semantic segmentation with multi-teacher knowledge distillation;Amirkhani;IEEE Access,2021

2. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

3. M3D-RPN: Monocular 3D region proposal network for object detection;Brazil,2019

4. Fast point R-CNN;Chen,2019

5. DSGN: Deep stereo geometry network for 3D object detection;Chen,2020

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1. DenseSphere: Multimodal 3D object detection under a sparse point cloud based on spherical coordinate;Expert Systems with Applications;2024-10

2. G-YOLO: A YOLOv7-based target detection algorithm for lightweight hazardous chemical vehicles;PLOS ONE;2024-04-24

3. The Research on Integrated Teaching System of Autonomous Driving Simulation;Proceedings of the 2023 International Conference on Information Education and Artificial Intelligence;2023-12-22

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