Official implementation of several experiments in the paper "**Π-nets: Deep Polynomial Neural Networks**" and its extension.

Each folder contains a different experiment. Please follow the instructions in the respective folder on how to run the experiments and reproduce the results. This repository contains implementations in MXNet, PyTorch and Chainer.

The folder structure is the following:

• face_recognition: The folder contains the code for the face verification and identification experiments.
• image_generation_chainer: The folder contains the image generation experiment on Chainer; specifically the experiment without activation functions between the layers.
• image_generation_pytorch: The folder contains the image generation experiment on PyTorch; specifically the conversion of a DCGAN-like generator into a polynomial generator.
• mesh_pi_nets: The folder contains the code for mesh representation learning with polynomial networks.

If you use this code, please cite [1]:

BibTeX:

@inproceedings{
poly2020,
title={$\Pi-$nets: Deep Polynomial Neural Networks},
author={Chrysos, Grigorios and Moschoglou, Stylianos and Bouritsas, Giorgos and Panagakis, Yannis and Deng, Jiankang and Zafeiriou, Stefanos},
booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}