Smart cities are expected to provide residents with convenience via various agents such as
CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data …

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 …

The quantification and improvement of safety is one of the most important objectives among
the general aviation community. In recent years, machine learning techniques have …

The goal of anomaly detection is to identify examples that deviate from normal or expected
behavior. We tackle this problem for images. We consider a two-phase approach. First …

The increasing popularity of compact and inexpensive cameras, eg dash cameras, body
cameras, and cameras equipped on robots, has sparked a growing interest in detecting …

Self-supervised learning allows for better utilization of unlabelled data. The feature
representation obtained by self-supervision can be used in downstream tasks such as …

Visual Teach-and-Repeat robot navigation suffers from environmental changes over time,
and it struggles in real-world long-term deployments. We propose a robust robot bearing …

We present an approach where a robot patrols a fixed path through an environment,
autonomously locating suspicious or anomalous objects. To learn, the robot patrols this …

We propose a semi-supervised model for detecting anomalies in videos inspiredby the
Video Pixel Network [van den Oord et al., 2016]. VPN is a probabilisticgenerative model …

We consider the problem of detecting, in the visual sensing data stream of an autonomous
mobile robot, semantic patterns that are unusual (ie, anomalous) with respect to the robot's …