AI RESEARCH
Drift-Resilient Temporal Priors for Visual Tracking
arXiv CS.CV
•
ArXi:2604.02654v1 Announce Type: new Temporal information is crucial for visual tracking, but existing multi-frame trackers are vulnerable to model drift caused by naively aggregating noisy historical predictions. In this paper, we