Created by Zengyi Qin, Jinglu Wang and Yan Lu. The repository contains an implementation of this AAAI Oral Paper.
Triangulation Learning Network: from Monocular to Stereo 3D Object Detection
Please cite this paper if you find the repository helpful:
@article{qin2019monogrnet,
title={MonoGRNet: A Geometric Reasoning Network for 3D Object Localization},
author={Zengyi Qin and Jinglu Wang and Yan Lu},
journal={The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)},
year={2019}
}
- Ubuntu 16.04
- Python 2.7
- Tensorflow 1.4.0
Clone this repository
git clone https://github.com/Zengyi-Qin/MonoGRNet.git
Download the Kitti Object Detection Dataset (image, calib and label) and place it into data/KittiBox
. The folder should be in the following structure:
data
KittiBox
training
calib
image_2
label_2
train.txt
val.txt
The train-val split train.txt
and val.txt
are contained in this repository.
Compile the Cython module and download the pretrained model:
python setup.py
Run the training script and specify the GPU to use:
python train.py --gpus 0
The evaluation is done during training. You can adjust the evaluation intervals in hypes/kittiBox.json
.
cd visualize && mkdir visualize
python visualize.py
We would like to thank the authors of KittiBox for their code.