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https://github.com/Vegeta2020/CIA-SSD
CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.
https://github.com/Vegeta2020/CIA-SSD
3d-object-detection autonomous-driving cia-ssd point-cloud-detection single-stage-detector
Last synced: 4 months ago
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CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.
- Host: GitHub
- URL: https://github.com/Vegeta2020/CIA-SSD
- Owner: Vegeta2020
- License: apache-2.0
- Created: 2020-12-02T12:59:03.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-11-06T09:42:22.000Z (over 1 year ago)
- Last Synced: 2024-01-16T05:32:03.978Z (5 months ago)
- Topics: 3d-object-detection, autonomous-driving, cia-ssd, point-cloud-detection, single-stage-detector
- Language: Python
- Homepage:
- Size: 860 KB
- Stars: 408
- Watchers: 12
- Forks: 65
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- Awesome-Autonomous-Driving - CIA-SSD - Confident IoU-Aware Single Stage Object Detector From Point Cloud. (3. Perception / 3.1.2 Lidar based)
- awesome-stars - Vegeta2020/CIA-SSD - CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021. (Python)
README
## CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud (AAAI 2021) [[Paper]](https://arxiv.org/abs/2012.03015)
Currently state-of-the-art single-stage object detector from point cloud on KITTI Benchmark, running with 32FPS.
**Authors**: [Wu Zheng](https://github.com/Vegeta2020), Weiliang Tang, Sijin Chen, [Li Jiang](https://github.com/llijiang), Chi-Wing Fu.
## TensorRT Version
A faster [TensorRT version](https://github.com/jingyue202205/CIA-SSD-AI-TRT) of CIA-SSD is going to be available thanks to [@jingyue202205](https://github.com/jingyue202205).
## AP on KITTI Dataset
Val Split (11 recall points):
```
Car AP:98.85, 90.20, 89.58
bev AP:90.51, 88.86, 87.95
3d AP:90.00, 79.86, 78.83
aos AP:98.77, 89.99, 89.24
Car AP(Average Precision)@0.70, 0.50, 0.50:
bbox AP:98.85, 90.20, 89.58
bev AP:98.92, 90.29, 89.81
3d AP:99.00, 90.22, 89.70
aos AP:98.77, 89.99, 89.24
```
Test Split: [Submission link](http://www.cvlibs.net/datasets/kitti/eval_object_detail.php?&result=b4e17f75f5baa917c4f250e832aace71682c3a84)
You may download the pre-trained model [here](https://drive.google.com/file/d/1SElYNQCsr4gctqLxmB6Fc4t7Ed8SgBgs/view?usp=sharing), which is trained on the train split (3712 samples).
## Pipeline
The pipeline of our proposed Confident IoU-Aware Single-Stage object Detector (CIA-SSD). First, we encode the input point cloud (a) with a sparse convolutional network denoted by SPConvNet (b), followed by our spatial-semantic feature aggregation (SSFA) module (c) for robust feature extraction, in which an attentional fusion module (d) is adopted to adaptively fuse the spatial and semantic features. Then, the multi-task head (e) realizes the object classification and localization, with our introduced confidence function (CF) for confidence rectification. In the end, we further formulate the distance-variant IoU-weighted NMS (DI-NMS) for post-processing.
## Installation
```bash
$ git clone https://github.com/Vegeta2020/CIA-SSD.git
$ cd ./CIA-SSD/det3d/core/iou3d
$ python setup.py install
$ cd ./CIA-SSD
$ python setup.py build develop
```
Please follow Det3D for installation of other [related packages](https://github.com/poodarchu/Det3D/blob/master/INSTALLATION.md) and [data preparation](https://github.com/poodarchu/Det3D/blob/master/GETTING_STARTED.md).
## Train and Eval
Configure the model in
```bash
$ /CIA-SSD/examples/second/configs/kitti_car_vfev3_spmiddlefhd_rpn1_mghead_syncbn.py
```
Please use our code to generate ground truth data:
```bash
$ python ./CIA-SSD/tools/create_data.py
```
Train the CIA-SSD:
```bash
$ cd ./CIA-SSD/tools
$ python train.py # Single GPU
$ python -m torch.distributed.launch --nproc_per_node=4 train.py # Multiple GPU
```
Evaluate the CIA-SSD:
```bash
$ cd ./CIA-SSD/tools
$ python test.py
```
## Citation
If you find this work useful in your research, please star our repository and consider citing:
```
@inproceedings{zheng2020ciassd,
title={CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud},
author={Wu Zheng, Weiliang Tang, Sijin Chen, Li Jiang, Chi-Wing Fu},
booktitle={AAAI},
year={2021}
}
```
## License
This codebase is released under the Apache 2.0 license.
## Acknowledgement
Our code are mainly based on [Det3D](https://github.com/poodarchu/det3d), thanks for their contributions! We also thank for the reviewers's valuable comments on this paper.
## Contact
If you have any question or suggestion about this repo, please feel free to contact me ([email protected])