Reproductionality Challenge 2020-2021 - Towards Visually Explaining Variational Autoencoders

Overview

This repository provides training and testing code and data for paper:

"Towards Visually Explaining Variational Autoencoders", Wenqian Liu, Runze Li, Meng Zheng, Srikrishna Karanam, Ziyan Wu, Bir Bhanu, Richard J. Radke, and Octavia Camps

Requirements

python 3.8.5
pytorch 1.7.0
torchvision 0.8.1
opencv 4.5.0
matplotlib 3.3.3
tqdm 4.56.0

You can easily install al dependencies with anaconda using

conda env create -f environment.yml

Running codes

Please use the corresponding notebook file to run all desired experiments. See Anomaly_Detection/ for the implementation of the anomaly detection and Latent_Space_Disentanglement/ for the implementation of the latent space disentanglement, and a more detailed description.