Oracle Analysis of Representations for Deep Open Set Detection

Understand

The problem of detecting a novel class at run time is known as Open Set Detection & is important for various real-world applications like medical application, autonomous driving, etc.

• Open Set Detection within context of deep learning involves solving two problems: (i) Must map the input images into a latent representation that contains enough information to detect the outliers, and (ii) Must learn an anomaly scoring function that can extract this information from the latent representation to identify the anomalies.
• Research in deep anomaly detection methods has progressed slowly.
• One reason may be that most papers simultaneously introduce new representation learning techniques and new anomaly scoring approaches.