The code base for M3DETR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
Tianrui Guan*, Jun Wang*, Shiyi Lan, Rohan Chandra, Zuxuan Wu, Larry Davis, Dinesh Manocha
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- A unified architecture for 3D object detection with transformers that accounts for multi-representation, multi-scale, mutual-relation models of point clouds in an end-to-end manner.
- Support major 3D object detection datasets: Waymo Open Dataset, KITTI.
See installation instructions.
See Getting Started with M3DETR.
We provide a large set of baseline results and trained models available for download in the M3DETR Model Zoo.
Please cite our work if you found it useful,
@InProceedings{Guan_2022_WACV,
author = {Guan, Tianrui and Wang, Jun and Lan, Shiyi and Chandra, Rohan and Wu, Zuxuan and Davis, Larry and Manocha, Dinesh},
title = {M3DETR: Multi-Representation, Multi-Scale, Mutual-Relation 3D Object Detection With Transformers},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages = {772-782}
}
This project is released under the Apache 2.0 license.
The source code of M3DETR is based on OpenPCDet.