leiup / mvcSnP

Code release for "Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction"

Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction

Shubham Tulsiani, Alexei A. Efros, Jitendra Malik.

Project Page

Installation

First, you'll need a working implementation of Torch. The subsequent installation steps are:

##### Install 3D spatial transformer ######
cd external/stn3d
luarocks make stn3d-scm-1.rockspec

##### Additional Dependencies (json and matio) #####
sudo apt-get install libmatio2
luarocks install matio
luarocks install json

Training and Evaluating

To train or evaluate the (trained/downloaded) models, it is first required to download the Shapenet dataset (v1) and preprocess the data to compute renderings and voxelizations. Please see the detailed README files for Training or Evaluation of models for subsequent instructions.

Demo and Pre-trained Models

To be added soon.

Citation

If you use this code for your research, please consider citing:

@article{mvcTulsiani18,
  title={Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction},
  author = {Shubham Tulsiani and Alexei A. Efros and Jitendra Malik},
  journal={arXiv},
  year={2018}
}