BGNet
This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]
Environment
- Python 3.6.*
- CUDA 10.1
- PyTorch 1.7.1
- TorchVision 0.8.2
Dataset
To evaluate/train our BGNet network, you will need to download the required datasets.
Pretrained model
We provide seven pretrained model under the folder models .
Evaluation
We provided a script to get the kitti benchmark result,check predict.sh for an example usage.
Prediction
We support predicting on any rectified stereo pairs. predict_sample.py provides an example usage.
Acknowledgements
Part of the code is adopted from the previous works: DeepPruner, GwcNet, GANet and AANet. We thank the original authors for their contributions.
Citing
If you find this code useful, please consider to cite our work.
@inproceedings{xu2021bilateral,
title={Bilateral Grid Learning for Stereo Matching Networks},
author={Xu, Bin and Xu, Yuhua and Yang, Xiaoli and Jia, Wei and Guo, Yulan},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={1--10},
year={2021}
}
