megdet3d's Introduction

MegDet3D

MEGVII's pytorch version 3D Object Detection codebase.

Introduction

MegDet3D is the first 3D Object Detection toolbox which provides off the box implementations of many 3D object detection algorithms such as PointPillars, SECOND, PointRCNN, PIXOR, etc, as well as state-of-the-art methods on major benchmarks like KITTI(ViP) and nuScenes(CBGS). Key features of MegDet3D include the following apects:

Multi Datasets Support: KITTI, nuScenes, Lyft, waymo
Point-based and Voxel-based model zoo
State-of-the-art performance
DDP & SyncBN

Benchmark

	KITTI(Val)	nuScenes(Val)
VoxelNet	-	-
SECOND	-	-
PointPillars	-	-
PIXOR	-	-
PointRCNN	-	-
CBGS	-	-
ViP	-	-

Installation

git clone https://github.com/poodarchu/MegDet3D --recursive
cd MegDet3D
pip install -r requirements.txt
python setup.py develop

Data preparation

Get Started

Implement your own methods

Contribute

Acknowledgement

Citation

@ARTICLE{2019arXiv190809492Z,
       author = {{Zhu}, Benjin and {Jiang}, Zhengkai and {Zhou}, Xiangxin and
         {Li}, Zeming and {Yu}, Gang},
        title = "{Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection}",
      journal = {arXiv e-prints},
     keywords = {Computer Science - Computer Vision and Pattern Recognition},
         year = "2019",
        month = "Aug",
          eid = {arXiv:1908.09492},
        pages = {arXiv:1908.09492},
archivePrefix = {arXiv},
       eprint = {1908.09492},
 primaryClass = {cs.CV},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190809492Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}