2022
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots
RA-L 2022
We consider the problem of building visual anomaly detection systems for mobile robots. Standard anomaly detection models are trained using large datasets composed only of non-anomalous data. However, in robotics applications, it is often the case that (potentially very few) examples of anomalies ar