OnPoint: Offline-to-Online Multi-Level Distillation for Point-Supervised Online Temporal Action Localization
arXiv cs.CV1mo4 min read
arXiv:2607.00289v1 Announce Type: new Abstract: Temporal Action Localization (TAL) typically relies on segment annotations or offline access to full videos, limiting scalability and online use. We introduce Point-Supervised Online TAL (POTAL), which localizes actions in streaming videos using only one temporal point per instance. To solve POTAL, we propose OnPoint, an offline-to-online multi-level distillation framework that transfers knowledge from a point-supervised offline teacher to an online student via (i) pseudo-segment instance distillation, (ii) class-activation sequence distillation,
