2.DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries DETR3D通过几何反投影和相机变换矩阵将 2D feature extraction 和3D object prediction 联系起来,在无需密集深度估计的情况下完成3D目标检测任务。将多视图检测转化为 set-to-set prediction 任务。 图2 DETR3D backbone:输入6个视角下...
Multi-View 3D Object Detection Network for Autonomous Driving 贡献点 利用多模态信息进行3D目标检测预测,融合主要思想是进行基于区域的特征融合。(不同view的ROI特征进行融合) MV3D包含两部分网络组成,剩下的就是对融合后的特征进行3D目标检测 3D Proposal Network 输入BEV视角下的点云,预测高质量的3D候选框。 3D...
实验表明,我们的3D建议明显优于最近的3D建议方法3DOP [4]和Mono3D [3]。特别地,在只有300个提案的情况下,我们在交并比(IoU)阈值为0.25和0.5的情况下分别获得了99.1%和91%的3D召回率。基于激光雷达的方法在三维定位任务中的精度提高了25%,在三维目标检测任务中的平均精度提高了30%。在KITTI的hard测试集上进行2D...
[论文解读]Multi-View 3D Object Detection Network for Autonomous Driving,程序员大本营,技术文章内容聚合第一站。
3D object detection in images 3DVP 利用3D voxel模式和利用ACF检测器进行2D检测和3D姿态估计。3DOP 使用熵最小化的方法从双目图像重构深度,然后输入到R-CNN用于目标识别。Mono3D和3DOP具有同样的pipeline,只不过是利用单目图像生成3D proposal。为了融合时序信息,一些工作结合运动中的结构以及地面估计将2D 目标检测迁...
3D点云做detection的一篇milestone paper。经典的two-stage方法(region proposal-based method)。思路来自于经典的faster rcnn。 整个模型如下图 图一. 整体模型 3D Point Cloud Representation 这篇文章可以归纳为是multiview-based method,multi-view的方法是指将三维点云按照不同view进行映射,得到很多的2D图像,因为...
Bird-eye-view (BEV) based methods have made great progress recently in multi-view 3D detection task. Comparing with BEV based methods, sparse based methods lag behind in performance, but still have lots of non-negligible merits. To push sparse 3D detection further, in this work, we introduce...
Multi-View 3D Object Detection Network for Autonomous Driving Xiaozhi Chen1, Huimin Ma1, Ji Wan2, Bo Li2, Tian Xia2 1Department of Electronic Engineering, Tsinghua University 2Baidu Inc. {chenxz12@mails., mhmpub@}tsinghua.edu.cn, {wanji, libo24, xiatian}@baidu.com Abstract This paper ...
Finally, we propose a multi-view branch-and-bound search algorithm for multi-view object detection. Through extensive experiments on three object categories, we show that object detection performance on X-ray images improves substantially with the help of extended features and multiple views. This ...
论文链接:Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion 代码链接:github.com/linxuewu/Spa 作者:Xuewu Lin, Tianwei Lin, Zixiang Pei, Lichao Huang, Zhizhong Su 发表单位:地平线 会议/期刊:无 一、研究背景 Sparse4D 概述。对于每个候选锚点实例,对多个关键点的多时间戳/视...