3D目标检测集合

一、基于图像

1.不需要额外数据输入

Deep3DBox
3D Bounding Box Estimation Using Deep Learning and Geometry
论文地址：https://arxiv.org/abs/1612.00496
代码地址：https://github.com/skhadem/3D-BoundingBox

GS3D
Gs3d: An efficient 3d object detection framework for autonomous driving
论文地址：https://arxiv.org/abs/1903.10955
代码地址：

MonoGRNet
Monogrnet: A geometric reasoning network for monocular 3d object localization.
论文地址：https://arxiv.org/pdf/1811.10247.pdf
代码地址：https://github.com/Zengyi-Qin/MonoGRNet

FQNet
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection
论文地址：https://arxiv.org/abs/1904.12681
代码地址：

M3D-RPN
M3D-RPN:Monocular 3D Region Proposal Network for Object Detection
论文地址：https://arxiv.org/abs/1907.06038v1
代码地址：https://github.com/garrickbrazil/M3D-RPN

2.基于立体信息

Mono3D

3.基于深度信息

3DOP

stereoRCNN

4.基于形状

MF3D

Peseudo-LiDAR

MonoPSR

AM3D

5.基于分割

Mono3D++

Deep-MENTA

3DVP

6.其他

Mono3D
3D Object Detection for Autonomous Driving: A Review and New Outlooks
论文地址：https://arxiv.org/abs/2206.09474
项目地址：https://xiaozhichen.github.io/

SubCNN
SubCNN: Subcategory-aware Convolutional Neural Networks for Object Proposals and Detection
论文地址：https://arxiv.org/abs/1604.04693v3
项目地址：https://github.com/tanshen/SubCNN

二、基于雷达