- python 3.6 (Anaconda)
pip install -r requirements.txt
- In
run.sh
, setroot_path
to the top directory, the organization is compatible with the outputs of UCSNet. If you want to process your custom data, please modify theload_data
function - Adjust
prob_thresh
,dist_thresh
andnum_consist
accordingly bash run.sh
This repository is a part of UCSNet, the code will be available after the paper be accepted. If you find this project useful for your research, please cite:
@inproceedings{cheng2020deep,
title={Deep stereo using adaptive thin volume representation with uncertainty awareness},
author={Cheng, Shuo and Xu, Zexiang and Zhu, Shilin and Li, Zhuwen and Li, Li Erran and Ramamoorthi, Ravi and Su, Hao},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={2524--2534},
year={2020}
}