CBiGAN: a combined model that generalizes Bidirectional GANs (BiGANs) and AutoEncoders, applied to anomaly detection in images. The repo provides training and evaluation code for the MVTecAD anomaly detection benchmark.

Also provides a TensorFlow2 implementation of BiGAN following the Wasserstein GAN (WGAN) formulation.

You need:

• Python 3
• Tensorflow 2.4.0
• packages in requirements.txt

You can use the Dockerfile to build an image.

Download the whole MVTec-AD dataset and extract into data/mvtec-ad.

Check out the train.py script for training parameters:

python train.py -h

Combining GANs and AutoEncoders for Efficient Anomaly Detection [arXiv] Fabio Carrara, Giuseppe Amato, Luca Brombin, Fabrizio Falchi, Claudio Gennaro

@article{carrara2020combining,
  title={Combining GANs and AutoEncoders for Efficient Anomaly Detection},
  author={Carrara, Fabio and Amato, Giuseppe and Brombin, Luca and Falchi, Fabrizio and Gennaro, Claudio},
  journal={arXiv preprint arXiv:2011.08102},
  year={2020}
}