Dense 3D Object Reconstruction from a Single Depth View
Bo Yang, Stefano Rosa, Andrew Markham, Niki Trigoni, Hongkai Wen. TPAMI, 2018.
(1) Architecture
(2) Sample Results
(3) Data
Part 1: {ShapeNetCore.v2: bench, chair, couch, table}, 20G
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
Real Dataset: {Kinect: bench, chair, couch, table}
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
All data and the trained model are also avaliable at Baidu Pan:
https://pan.baidu.com/s/1FQXo_XQX4flDrE_jwElCCw ζεη : 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}
}