no code implementations • 3 Jul 2022 • Vahid Reza Khazaie, Anthony Wong, John Taylor Jewell, Yalda Mohsenzadeh
The Adversarial Distorter is a convolutional encoder that learns to produce effective perturbations and the autoencoder is a deep convolutional neural network that aims to reconstruct the images from the perturbed latent feature space.
1 code implementation • 27 Mar 2021 • John Taylor Jewell, Vahid Reza Khazaie, Yalda Mohsenzadeh
In particular, context autoencoders have been successful in the novelty detection task because of the more effective representations they learn by reconstructing original images from randomly masked images.
Ranked #28 on Anomaly Detection on One-class CIFAR-10