ACMM

KO | EN

gitlite — search

#javascript #hacktoberfest #typescript #go #machine-learning #rust #deep-learning #docker #macos #nodejs #windows #kubernetes #pytorch #security

(★ 162)

Multi-Scale Geometric Consistency Guided Multi-View Stereo

파일 탐색기

최종 버전 다운로드 (.zip)

ACMM.cpp
ACMM.cu
ACMM.h
CMakeLists.txt
colmap2mvsnet_acm.py
LICENSE
main.cpp
main.h
README.md

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# ACMM
[News] The code for [ACMH](https://github.com/GhiXu/ACMH) is released!!!  
[News] The code for [ACMP](https://github.com/GhiXu/ACMP) is released!!!  
[News] The code for [ACMMP](https://github.com/GhiXu/ACMMP) is released!!!  
## About
[ACMM](https://arxiv.org/abs/1904.08103) 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.  
* [Cuda](https://developer.nvidia.com/zh-cn/cuda-downloads) >= 6.0
* [OpenCV](https://opencv.org/) >= 2.4
* [cmake](https://cmake.org/)
## Usage
* Compile ACMM
```  
cmake .  
make
```
* Test 
``` 
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    |
## SfM Reconstructions for Tanks and Temples Dataset
To ease comparison with other MVS methods with our method on [Tanks and Temples dataset](https://www.tanksandtemples.org/), we release our SfM reconstuctions on this dataset. They are obtained by [COLMAP](https://colmap.github.io/) and can be downloaded from [here](https://drive.google.com/open?id=1DTnnmJAOGt7WPXSLMysMvPTy4CUZt_TU).
## Acknowledgements
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.

ACMM

파일 탐색기

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

ACMM

파일 탐색기

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README