Multi-Scale Geometric Consistency Guided Multi-View Stereo
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ACMM
ACMM is a multi-scale geometric consistency guided multi-view stereo method for efficient and accurate depth map estimation. If you find this project useful for your research, please cite:
@article{Xu2019ACMM,
title={Multi-Scale Geometric Consistency Guided Multi-View Stereo},
author={Xu, Qingshan and Tao, Wenbing},
journal={Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}
Dependencies
The code has been tested on Ubuntu 14.04 with GTX Titan X.
Usage
cmake .
make
Use script colmap2mvsnet_acm.py to convert COLMAP SfM result to ACMM input
Run ./ACMM $data_folder to get reconstruction results
Results on high-res ETH3D training dataset [2cm]
Mean | courtyard | delivery_area | electro | facade | kicker | meadow | office | pipes | playgroud | relief | relief_2 | terrace | terrains |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
78.87 | 87.47 | 83.70 | 86.82 | 70.79 | 77.51 | 66.41 | 64.88 | 70.07 | 72.06 | 85.36 | 84.87 | 89.85 | 85.52 |