# ACMP

**Repository Path**: yezhiyun/ACMP

## Basic Information

- **Project Name**: ACMP
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-03-08
- **Last Updated**: 2022-03-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ACMP
[News] The code for [ACMH](https://github.com/GhiXu/ACMH) is released!!!  
[News] The code for [ACMM](https://github.com/GhiXu/ACMM) is released!!!  
[News] The code for [ACMMP](https://github.com/GhiXu/ACMMP) is released!!!  
## About
This repository contains the code for the paper [Planar Prior Assisted PatchMatch Multi-View Stereo](https://arxiv.org/abs/1912.11744), Qingshan Xu and Wenbing Tao, AAAI2020. If you find this project useful for your research, please cite:  
```
@article{Xu2020ACMP,  
  title={Planar Prior Assisted PatchMatch Multi-View Stereo}, 
  author={Xu, Qingshan and Tao, Wenbing}, 
  journal={AAAI Conference on Artificial Intelligence (AAAI)},
  year={2020}
}
@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.  
* [Cuda](https://developer.nvidia.com/zh-cn/cuda-downloads) >= 6.0
* [OpenCV](https://opencv.org/) >= 2.4
* [cmake](https://cmake.org/)
## Usage
* Complie ACMP
```  
cmake .  
make
```
* Test 
``` 
Use script colmap2mvsnet_acm.py to convert COLMAP SfM result to ACMP input   
Run ./ACMP $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 |
|--------|-----------|---------------|---------|--------|--------|--------|--------|--------|-----------|--------|----------|---------|----------|
| 79.81  | 86.57     | 85.04         | 86.83   | 69.88  | 77.01  | 64.88  | 75.81	 | 71.13  | 71.14     | 84.46  | 84.16    | 90.14	  | 90.50    |
## Acknowledgemets
This code largely benefits from the following repositories: [Gipuma](https://github.com/kysucix/gipuma) and [COLMAP](https://colmap.github.io/). Thanks to their authors for opening source of their excellent works.