Novelty Detection via Non-Adversarial Generative Network

Understand

One-class novelty detection is the process of determining if a query example differs from the training examples (the target class).

• Most of previous strategies attempt to learn the real characteristics of target sample by using generative adversarial networks (GANs) methods.
• However, the training process of GANs remains challenging, suffering from instability issues such as mode collapse and vanishing gradients.
• In this paper, by adopting non-adversarial generative networks, a novel decoder-encoder framework is proposed for novelty detection task, insteading of classical encoder-decoder style.