[CVPR 2022] Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation

Jiankun Li, Peisen Wang, Pengfei Xiong, Tao Cai, Ziwei Yan, Lei Yang, Jiangyu Liu, Haoqiang Fan, Shuaicheng Liu

arXiv | BibTeX

Datasets

The Proposed Dataset

Download

There are two ways to download the dataset(~400GB) proposed in our paper:

• Download using shell scripts dataset_download.sh

sh dataset_download.sh

• Download from BaiduCloud here(Extraction code: aa3g) and extract the tar files manually.

Disparity Format

The disparity is saved as .png uint16 format which can be loaded using opencv imread function:

def get_disp(disp_path):
    disp = cv2.imread(disp_path, cv2.IMREAD_UNCHANGED)
    return disp.astype(np.float32) / 32

Other Public Datasets

Other public datasets we use including

• SceneFlow
• Sintel
• Middlebury
• ETH3D
• KITTI 2012/2015
• Falling Things
• InStereo2K
• HR-VS

Citation

If you find this work helpful in your research, please cite:

@misc{Li2022crestereo,
      title={Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation},
      author={Jiankun Li and Peisen Wang, Pengfei Xiong and Tao Cai and Ziwei Yan and Lei Yang and Jiangyu Liu and Haoqiang Fan and Shuaicheng Liu},
      year={2022},
      eprint={2203.11483},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}