实验结果表明,本文提出的网络优于以前的所有基于立体的3D探测器(AP大约高10个),甚至在KITTI 3D目标检测排行榜上与一些基于LiDAR的方法性能不相上下。 CNNer 2020/06/19 7120 伪激光雷达:无人驾驶的立体视觉 人工智能 激光雷达成本高,用廉价的立体视觉替代它可行吗?作者:Jeremy Cohen 编译:McGL McGL 2020/09/...
首先利用DRON或PSMNET从单目(Monocular)或双目(Stereo)图像获取对应的深度图像(depth map),然后将原图像结合深度信息得到伪雷达点云(pseudo-LiDAR),最后用pseudo-LiDAR代替原始雷达点云,以3D point cloud和bird's eye view的形式,分别在LiDAR-based的F-PointNet以及AVOD上与图像的front view表示进行了比较,并对比了Ima...
文章标题:Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving 文章链接:https://arxiv.org/abs/1812.07179 代码链接:https://github.com/mileyan/pseudo_lidar 名词解释: Pseudo-LiDAR(伪激光点云),即通过双目或者单目视觉获取的深度信息,经过投影变换,将每...
3D点云:frustum PointNet; 从Bird's Eye View(BEV)角度去观察pseudo-LiDAR数据:这样从俯视角度,3D信息被转化成为2D图像(保留宽和深,高度存在通道中),AVOD。 数据表示形式至关重要: 尽管pseudo-LiDAR和深度图中是相同的信息转化而来,但是本文主张pseudo-LiDAR数据更适用于基于卷积神经网络的3D目标检测。 卷积神经网络...
Image pseudo-LiDARCoordinate transformationThe recently proposed pseudo-LiDAR based 3D detectors greatly improve the benchmark of monocular/stereo 3D detection task. However, the underlying mechanism remains obscure to the research community. In this paper, we perform an in-depth investigation and ...
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving Yurong,程序员大本营,技术文章内容聚合第一站。
代码链接:https://github.com/mileyan/pseudo_lidar 摘要 3D目标检测是一个重要的任务在自动驾驶领域。最近高精度检测率技术清单中,提供3D输入数据被提供从精确但是昂贵的LiDAR(激光雷达)技术。方法基于便宜的单目或者立体图像数据,直到现在,结果全部都是低精度-一个问题比较常见地导致是基于图像深度估...
课件成果介绍pseudo lidar from visual depth estimation bridging the gap 3d object detection for autonomous driving.pdf,Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving Yan Wang, Wei-Lun Chao, Divyan
具体来说,执行单目深度估计并将输入图像提升到伪激光雷达(pseudo-LiDAR)点云的表示形式,然后...信息来,然后利用单目深度将2D图片投射到3D空间,从而模拟雷达点云信号,之后可以利用基于点云的3D目标检测算法。 二、单目3D目标检测算法解析2.1基于图片的方法:D4LCN-学习深度引导卷积单...
End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection This paper has been accepted by Computer Vision and Pattern Recognition 2020. End-to-end Pseudo-LiDAR for Image-Based 3D Object Detection by Rui Qian*, Divyansh Garg*, Yan Wang*, Yurong You*, Serge Belongie, Bharath Hariharan, Ma...