Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection
groomed_nms
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection
CVPR 2021
Abhinav Kumar, Garrick Brazil, Xiaoming Liu
project, supp, 5min_talk, slides, demo, poster, arxiv
This code is based on Kinematic-3D, such that the setup/organization is very similar. A few of the implementations, such as classical NMS, are based on Caffe.
References
Please cite the following paper if you find this repository useful:
@inproceedings{kumar2021groomed,
title={{GrooMeD-NMS}: Grouped Mathematically Differentiable NMS for Monocular {$3$D} Object Detection},
author={Kumar, Abhinav and Brazil, Garrick and Liu, Xiaoming},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2021}
}
Setup
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Requirements
- Python 3.6
- Pytorch 0.4.1
- Torchvision 0.2.1
- Cuda 8.0
- Ubuntu 18.04/Debian 8.9
This is tested with NVIDIA 1080 Ti GPU. Other