OnPoint enables point-supervised online temporal action localization by distilling pseudo-segments, class-activation sequences, and anticipatory windows from an offline teacher to an online student.
In: Proceedings of the ieee conference on computer vision and pattern recognition
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2representative citing papers
A large-scale, hierarchically-annotated human-centric video dataset and a three-level benchmark (OHBench) are presented, showing that fine-tuning on a subset of the data improves audio-video generation model performance.
citing papers explorer
-
OnPoint: Offline-to-Online Multi-Level Distillation for Point-Supervised Online Temporal Action Localization
OnPoint enables point-supervised online temporal action localization by distilling pseudo-segments, class-activation sequences, and anticipatory windows from an offline teacher to an online student.
-
OmniHuman: A Large-scale Dataset and Benchmark for Human-Centric Video Generation
A large-scale, hierarchically-annotated human-centric video dataset and a three-level benchmark (OHBench) are presented, showing that fine-tuning on a subset of the data improves audio-video generation model performance.