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The implementation of "Joint Texture and Geometry Optimization for RGB-D Reconstruction (CVPR2020)"

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JointTG

This repository contains the implementation of "Joint Texture and Geometry Optimization for RGB-D Reconstruction (CVPR2020)" based on Open3D. Due to the agreement with other company, some parts can only be released in the form of .so files. More information and the paper can be found on our group website and Qingan's homepage.

Publication

If you find this code useful for your research, please cite our work:

Yanping Fu, Qingan Yan, Jie Liao, Chunxia Xiao. Joint Texture and Geometry Optimization for RGB-D Reconstruction. In CVPR. 2020.

@inproceedings{fu2020joint,
  title={Joint Texture and Geometry Optimization for RGB-D Reconstruction},
  author={Fu, Yanping and Yan, Qingan and Liao, Jie and Xiao, Chunxia},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={5950--5959},
  year={2020}
}

How to use

1. Run

To test our algorithm. run G2LTex in command line:

./bin/JointTG [IAMGESDIR] [PLY] [TRAJECTORY] 

Params explanation:

-`IAMGESDIR`:The texture image directory, include rgb images, depth images.
-`PLY`: The reconstructed model for texture mapping.
-`TRAJECTORY`:  The camera pose of each key-frame.

The parameters of the camera and the system can be set in the config file.

Config/config.yml

How to install and run this code.

git clone https://github.com/fdp0525/JointTG.git
cd JointTG/bin
./JointTG ./bricks/images ./bricks/bricks-fusion.ply ./bricks/traj.log

We need to modify the configuration file config.yml before running the other datasets.

2. Dependencies

The code has following prerequisites:

  • ubuntu 16.04
  • gcc (5.4.0)
  • OpenCV (2.4.10)
  • Eigen (>3.0)
  • Flann (1.9.1)

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