In many object recognition applications, the set of possible categories is an open set, and deployed system will encounter novel objects belonging to unseen during training. Detecting such “novel category” usually formulated as anomaly detection problem. Anomaly algorithms for feature-vector data identify anomalies outliers, but outlier has not worked well in deep learning. Instead, methods bas...