This repository contains pre-trained models and evaluation code for the project 'Single Image 3D Interpreter Network' (ECCV 2016).
http://3dinterpreter.csail.mit.edu
We use Torch 7 (http://torch.ch) for our implementation.
We use .mat
file with fb.mattorch
for saving results, and Matlab
(R2015a or later, with Computer Vision System Toolbox) for visualization.
Our current release has been tested on Ubuntu 14.04.
git clone git@github.com:jiajunwu/3dinn.git
cd 3dinn
./download_models.sh
The file (src/main.lua
) has the following options.
-gpuID
: specifies the gpu to run on (1-indexed)-class
: which model to use for evaluation. Our current release contains four models:chair
,swivelchair
,bed
, andsofa
.-batchSize
: the batch size to use
Sample usages include
- Estimate chair structure for images listed in
data/class.txt
cd src
th main.lua -gpuID 1 -class chair
-
Keypoint-5 dataset (zip, 208MB)
-
Extended IKEA dataset with additional 3D keypoint labels (zip, 171MB)
@inproceedings{3dinterpreter,
title={{Single Image 3D Interpreter Network}},
author={Wu, Jiajun and Xue, Tianfan and Lim, Joseph J and Tian, Yuandong and Tenenbaum, Joshua B and Torralba, Antonio and Freeman, William T},
booktitle={European Conference on Computer Vision},
pages={365--382},
year={2016}
}
For any questions, please contact Jiajun Wu (jiajunwu@mit.edu) and Tianfan Xue (tfxue@mit.edu).