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Suppress-and-Refine Framework for End-to-End 3D Object Detection

This repo is the official implementation of "Suppress-and-Refine Framework for End-to-End 3D Object Detection".

A simple, fast, efficient and end-to-end 3D object detector without NMS.

Getting Started

Main results

ScanNet V2

Method backbone [email protected] [email protected] Runtime (FPS) Ckpt
VoteNet PointNet++ 62.9 39.9 10.8 -
H3DNet 4xPointNet++ 67.2 48.1 4.4 -
MLCVNet PointNet++ 64.5 41.4 6.7 -
BRNet PointNet++ 66.1 50.9 8.7 -
Group-Free PointNet++ 67.3 48.9 7.1 -
Ours PointNet++ 66.2 53.5 13.5 model_ckpt

SUN RGB-D

Method backbone [email protected] [email protected] Ckpt
VoteNet PointNet++ 59.1 35.8 -
H3DNet 4xPointNet++ 60.1 39.0 -
MLCVNet PointNet++ 59.8 - -
BRNet PointNet++ 61.1 43.7 -
Group-Free PointNet++ 63.0 45.2 -
Ours PointNet++ 60.0 44.7 model_ckpt

The FPS is tested on a V100 GPU.

Quick start

Installation

This repository is based on mmdetection3d, please follow this page for installation guidance.

Reproduce our results on SCANNET and SUNRGBD

For SCANNET.

CUDA_VISIBLE_DEVICES=0,1 PORT=29600 ./tools/dist_train.sh configs/sr/scannet_baseline.py 2

For SUNRGBD

CUDA_VISIBLE_DEVICES=0,1 PORT=29600 ./tools/dist_train.sh configs/sr/sunrgbd_baseline.py 2
Evaluation

Please first download the ckpt from the ckpt link provided above.

Then for SCANNET.

./tools/dist_test.sh configs/sr/scannet_baseline.py epoch_30.pth 2 --eval mAP

For SUNRGBD

./tools/dist_test.sh configs/sr/sunrgbd_baseline.py epoch_33.pth 4 --eval mAP

Acknowledgement

Our code is based on wonderful mmdetection3d. Very apperciate their works!

Citation

If you find this project useful in your research, please consider cite:

@article{liu2021suppress,
  title={Suppress-and-Refine Framework for End-to-End 3D Object Detection},
  author={Liu, Zili and Xu, Guodong and Yang, Honghui and Chen, Minghao and Wu, Kuoliang and Yang, Zheng and Liu, Haifeng and Cai, Deng},
  journal={arXiv preprint arXiv:2103.10042},
  year={2021}
}