Leveraging Shape Completion for 3D Siamese Tracking

Supplementary Code for the CVPR'19 paper entitled Leveraging Shape Completion for 3D Siamese Tracking

Citation

@InProceedings{Giancola_2018_CVPR,
author = {Giancola, Silvio and Zarzar, Jesus and Ghanem, Bernard},
title = {Leverage Shape Completion for 3D Siamese Tracking},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}

Usage

Download KITTI Tracking dataset

Download the dataset from KITTI Tracking.

You will need to download the data for velodyne, calib and label_02.

Place the 3 folders in the same parent folder as following:

[Parent Folder]
--> [calib]
    --> {0000-0020}.txt
--> [label_02]
    --> {0000-0020}.txt
--> [velodyne]
    --> [0000-0020] folders with velodynes .bin files

Create Environment

conda create -y -n ShapeCompletion3DTracking python tqdm numpy pandas shapely matplotlib pomegranate
source activate ShapeCompletion3DTracking
conda install -y pytorch=0.4.1 cuda90 -c pytorch
pip install pyquaternion

Train a model

python main.py --train_model --model_name=<Name of your model> --dataset_path=<Path to KITTI Tracking folder>

Test a model

python main.py --test_model --model_name=<Name of your model> --dataset_path=<Path to KITTI Tracking folder>

Options

Run python main.py --help for a detailled description of the parameters.

OPT:
    --model_name=<Name of your model>
    --dataset_path=<Path to KITTI Tracking>
    --lambda_completion=1e-6: balance between tracking and completion loss
    --bneck_size=128: lenght of the latent vector
    --GPU=1: enforce the use of GPU 1 
    --tiny: use a tiny set of KITTI Tracking

huanglianghua / ShapeCompletion3DTracking