This is the implementation of the paper Group-wise Correlation Stereo Network, CVPR 19, Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, and Hongsheng Li [Arxiv]
- python 3.6
- Pytorch >= 0.4.1
Download Scene Flow Datasets, KITTI 2012, KITTI 2015
Scene Flow Datasets
run the script ./scripts/sceneflow.sh to train on Scene Flow datsets. Please update DATAPATH in the bash file as your training data path.
KITTI 2012 / 2015
run the script ./scripts/kitti12.sh and ./scripts/kitti15.sh to finetune on the KITTI 12/15 dataset. Please update DATAPATH and --loadckpt as your training data path and pretrained SceneFlow checkpoint file.
run the script ./scripts/kitti12_save.sh and ./scripts/kitti15_save.sh to save png predictions on the test set of the KITTI datasets to the folder ./predictions.
If you find this code useful in your research, please cite:
@inproceedings{guo2019group,
title={Group-wise Correlation Stereo Network},
author={Guo, Xiaoyang and Yang, Kai and Yang, Wukui and Wang, Xiaogang and Li, Hongsheng},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
pages={3273--3282},
year={2019}
}
Thanks to Jia-Ren Chang for opening source of his excellent work PSMNet. Our work is inspired by this work and part of codes in models are migrated from PSMNet.
