每天一篇论文 320/365 LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving

时间 2021-01-02

标签每天一篇论文365 繁體版

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LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving 摘要本文提出了一种基于激光雷达数据的自动驾驶三维目标检测算法LaserNet。效率来自于在传感器的原始范围视图中处理激光雷达数据，在该视图中，输入数据自然紧凑。在范围视图中操作涉及到众所周知的学习挑战，包括遮挡和尺度变化，但它也提供了基于如

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1. 每天一篇论文 373/1000 PSEUDO-LIDAR++:ACCURATE DEPTH FOR 3D OBJECT DETECTION IN AUTONOMOUS DRIVING
2. 每天一篇论文 324/365RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving
3. Multi-View 3D Object Detection Network for Autonomous Driving
4. Stereo R-CNN based 3D Object Detection for Autonomous Driving
5. 论文阅读CVPR2019——Stereo R-CNN based 3D Object Detection for Autonomous Driving
6. [论文解读]Multi-View 3D Object Detection Network for Autonomous Driving
7. Pillar-based Object Detection for Autonomous Driving
8. 【3D目标检测】Multi-View 3D Object Detection Network for Autonomous Driving论文综述（2016）
9. 论文笔记_CV_AD_Visual Perception for Autonomous Driving
10. 解读ECCV2020：Pillar-based Object Detection for Autonomous Driving

>>更多相关文章<<