Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks
N Dinesh Reddy, Minh Vo, Srinivasa G. Narasimhan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[Project] [Paper] [Supp] [Bibtex ]
More Results
Result of Occlusion-Net on a live video from youtube
Installation
Setting up with docker
All the stable releases of docker-ce installed from https://docs.docker.com/install/
Install the nvidia-docker from https://github.com/NVIDIA/nvidia-docker
Setting up the docker
nvidia-docker build -t occlusion_net .Setting up data
You need to fill the Access Form to get a email regarding the dataset and setup at using the following commands:
git clone https://github.com/dineshreddy91/carfusion_to_coco
cd carfusion_to_coco
virtualenv carfusion2coco -p python3.6
source carfusion2coco/bin/activate
pip install cython numpy
pip install -r requirements.txt
python download_carfusion.py (This file need to be downloaded by requesting, please fill to get access to the data)
sh carfusion_coco_setup.sh
deactivate
The final folder format to train on carfusion data needs to look :
Occlusion-Net
└─datasets
└─carfusion
└─train
└─car_craig1
└───images
01_0000.jpg
01_0001.jpg
...
└───bb
01_0000.txt
01_0001.txt
...
└───gt
01_0000.txt
01_0001.txt
...
└─test
└─car_penn1
└───images
01_0000.jpg
01_0001.jpg
...
└───bb
01_0000.txt
01_0001.txt
...
└───gt
01_0000.txt
01_0001.txt
...
└─annotations
car_keypoints_train.json
car_keypoints_test.json
Running with docker
Training the model on the carfusion dataset
sh train.sh occlusion_net <Path_to_Carfusion_dataset>
Testing on a sample image
Download a pretrained model from [Google Drive]
Results on a sample demo image
sh test.sh occlusion_net demo/demo.jpg
Citation
@inproceedings{onet_cvpr19,
author = {Reddy, N. Dinesh and Vo, Minh and Narasimhan, Srinivasa G.},
title = {Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
pages = {7326--7335},
year = {2019}
}
@InProceedings{Reddy_2018_CVPR,
author = {Dinesh Reddy, N. and Vo, Minh and Narasimhan, Srinivasa G.},
title = {CarFusion: Combining Point Tracking and Part Detection for Dynamic 3D Reconstruction of Vehicles},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}