1 citations · 1 across the 3 of their papers we have counts for
3 papers
FlowCLAS: Enhancing Normalizing Flow Via Contrastive Learning For Anomaly Segmentation
Chang Won Lee, Selina Leveugle, Svetlana Stolpner +4
Anomaly segmentation is an essential capability for safety-critical robotics applications that must be aware of unexpected events. Normalizing flows (NFs), a class of generative mo…
A Photorealistic Dataset and Vision-Based Algorithm for Anomaly Detection During Proximity Operations in Lunar Orbit
Selina Leveugle, Chang Won Lee, Svetlana Stolpner +4
NASA's forthcoming Lunar Gateway space station, which will be uncrewed most of the time, will need to operate with an unprecedented level of autonomy. One key challenge is enabling…
UncertaintyTrack: Exploiting Detection and Localization Uncertainty in Multi-Object Tracking
Chang Won Lee, Steven L. Waslander
Multi-object tracking (MOT) methods have seen a significant boost in performance recently, due to strong interest from the research community and steadily improving object detectio…