7、PIXOR: Real-time 3D Object Detection from Point Clouds 8、Complex-YOLO: An Euler-Region-Proposal for Real-time 3D Object Detection on Point Clouds 9、YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud 10、Vehicle Detection from 3D Lidar Using FC...
具体地,整体网络框架流程可以描述为:输入RGB图像得到2D检测结果,将其映射为3D视锥区域,在视锥区域内进行前背景点及3D box预测。 As shown in the Figure, our system for 3D object detection consists of three modules: frustum proposal, 3D instance segmentation, and 3D amodal bounding box estimation. 主要...
9、PointFusion:Deep Sensor Fusion for 3D Bounding Box Estimation 10、Pseudo-LiDAR from Visual Depth Estimation:Bridging the Gap in 3D Object Detection for Autonomous Driving 三、基于激光雷达点云的3D目标检测 1、VoteNet 2、End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds ...
论文汇总 (1)FCOS3D: Fully Convolutional One-stage Monocular 3D Object Detection (1st place of NIPS 2020 vision-only nuScenes 3D detection) 论文主要基于FCOS无锚点2D目标检测做的改进,backbone为带有DCN的ResNet101,并配有FPN架构用于检测不同尺度的目标,网络结构如图1所示: 图1 FCOS3D网络架构图 分类分支...
解读:浙大和商汤等提出:Libra RCNN目标检测新算法(特征融合),CVPR2019 20、Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition作者:Moein Shakeri, Hong Zhang 论文链接:https://arxiv.org/abs/1904.0317521、Towards Universal Object Detection...
对于3D目标的中心坐标、高、宽、长和偏航角的预测，网络通过回归偏航角时预测方向类别来增强定位准确性。回归任务形式化表示为预测深度、方向速度等参数。SMOKE论文是对CenterNet在单目3D目标检测方向的拓展，主干采用带有DCN和GN标准化的DLA-34神经网络提取特征。关键点预测分支定位前景目标，通过网络输出高斯核...
论文框架主要包括三部分,二维结构多边形估计、高度引导的深度估计、3D检测框提炼,网络结构如下图1所示: 图1 Decoupled-3d 网络框架 多边形估计 网络首先基于2D目标检测任务,将检测出的目标crop出来,然后通过相机坐标系-图像坐标系的转换公式,将目标在相机坐标系下的8个角点映射到图像坐标系下,然后网络针对crop的图像做...
Code: GitHub - mengtan00/SA-BEV: This is the implementation of the paper "SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection" (ICCV 2023) 北航 HoP: Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction Paper:...