Systems and methods for partially supervised online action detection in untrimmed videos
US12299982B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 16, 2020 |
| Grant date | May 13, 2025 |
| Priority date | — |
| Expiry date | Jan 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide systems and methods for a partially supervised training model for online action detection. Specifically, the online action detection framework may include two modules that are trained jointly—a Temporal Proposal Generator (TPG) and an Online Action Recognizer (OAR). In the training phase, OAR performs both online per-frame action recognition and start point detection. At the same time, TPG generates class-wise temporal action proposals serving as noisy supervisions for OAR. TPG is then optimized with the video-level annotations. In this way, the online action detection framework can be trained with video-category labels only without pre-annotated segment-level boundary labels.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.