AI RESEARCH
Clip-level Uncertainty and Temporal-aware Active Learning for End-to-End Multi-Object Tracking
arXiv CS.CV
•
ArXi:2605.09858v1 Announce Type: new Multi-Object Tracking (MOT) in dynamic environments relies on robust temporal reasoning to maintain consistent object identities over time. Transformer-based end-to-end MOT models achieve strong performance by explicitly modeling temporal dependencies, yet