Sign-Agnostic Optimization of Convolutional Occupancy Networks

This repository contains the implementation of the paper:

Sign-Agnostic CONet: Learning Implicit Surface Reconstructions by Sign-Agnostic Optimization of Convolutional Occupancy Networks
ICCV 2021 (Oral)

If you find our code or paper useful, please consider citing

@inproceedings{tang2021sign,
  title={SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks},
  author={Tang, Jiapeng and Lei, Jiabao and Xu, Dan and Ma, Feiying and Jia, Kui and Zhang, Lei},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  year={2021}
}

Contact Jiapeng Tang for questions, comments and reporting bugs.

Installation

First you have to make sure that you have all dependencies in place.
The simplest way to do so, is to use anaconda.

You can create an anaconda environment called sa_conet using

conda env create -f environment.yaml
conda activate sa_conet

Note:

 

 

 

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