https://github.com/Yang7879/3D-RecGAN-extended

🔥3D-RecGAN++ in Tensorflow (TPAMI 2018)
https://github.com/Yang7879/3D-RecGAN-extended

3d-computer-vision 3d-reconstruction gans generative-adversarial-network shapenetcore

Last synced: 2 months ago
JSON representation

🔥3D-RecGAN++ in Tensorflow (TPAMI 2018)

• Host: GitHub
• URL: https://github.com/Yang7879/3D-RecGAN-extended
• Owner: Yang7879
• License: mit
• Created: 2018-01-30T16:36:38.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2019-08-17T06:18:14.000Z (over 5 years ago)
• Last Synced: 2024-08-01T03:43:45.727Z (5 months ago)
• Topics: 3d-computer-vision, 3d-reconstruction, gans, generative-adversarial-network, shapenetcore
• Language: Python
• Homepage: https://arxiv.org/abs/1802.00411
• Size: 10.2 MB
• Stars: 133
• Watchers: 12
• Forks: 29
• Open Issues: 16
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Dense 3D Object Reconstruction from a Single Depth View

Bo Yang, Stefano Rosa, Andrew Markham, Niki Trigoni, Hongkai Wen. [TPAMI](http://dx.doi.org/10.1109/TPAMI.2018.2868195), 2018.

## (1) Architecture

![Arch_Image](https://github.com/Yang7879/3D-RecGAN-extended/blob/master/3D-RecGAN%2B%2B_arch.png)

## (2) Sample Results

![Teaser_Image](https://github.com/Yang7879/3D-RecGAN-extended/blob/master/3D-RecGAN%2B%2B_sample.png)

## (3) Data

#### Part 1: {ShapeNetCore.v2: bench, chair, couch, table}, 20G

[https://drive.google.com/open?id=1rmOggF0ivB42KozMX3sQGD1CkZNOGCmM](https://drive.google.com/open?id=1rmOggF0ivB42KozMX3sQGD1CkZNOGCmM)

#### Part 2: {ShapeNetCore.v2: airplane, car, monitor, faucet, guitar, gun}, 9.3G

[https://drive.google.com/open?id=1zLQd68O73ZiwZ8S8qsLwwGYDcC5PiEdG](https://drive.google.com/open?id=1zLQd68O73ZiwZ8S8qsLwwGYDcC5PiEdG)

#### Real Dataset: {Kinect: bench, chair, couch, table}

[https://drive.google.com/open?id=1wTE721q0r66Z6yyN68O1Tz4Bg5-aYnq3](https://drive.google.com/open?id=1wTE721q0r66Z6yyN68O1Tz4Bg5-aYnq3)

## (4) Released Model

#### Trained on {bench, chair, couch, table}, 2G

[https://drive.google.com/open?id=1IzwZLgRhzd6GVofzdjBZTblxMPH7NuxP](https://drive.google.com/open?id=1IzwZLgRhzd6GVofzdjBZTblxMPH7NuxP)

##### All data and the trained model are also avaliable at Baidu Pan:

[https://pan.baidu.com/s/1FQXo_XQX4flDrE_jwElCCw](https://pan.baidu.com/s/1FQXo_XQX4flDrE_jwElCCw) 提取码: cam7

## (5) Requirements

python 2.7.6

tensorflow 1.2.0

numpy 1.13.3

scipy 0.19.0

matplotlib 2.0.2

skimage 0.13.0

## (6) Run

#### Training

python main_3D-RecGAN++.py

#### Test Demo (Download released model first)

python demo_3D-RecGAN++.py

## (7) Citation

If you use the paper, code or data for your research, please cite:

```

@inProceedings{Yang18,

  title={Dense 3D Object Reconstruction from a Single Depth View},

  author = {Bo Yang

  and Stefano Rosa

  and Andrew Markham

  and Niki Trigoni

  and Hongkai Wen},

  booktitle={TPAMI},

  year={2018}

}

```