Invention Grant
- Patent Title: Active learning method for temporal action localization in untrimmed videos
-
Application No.: US15957419Application Date: 2018-04-19
-
Publication No.: US10726313B2Publication Date: 2020-07-28
- Inventor: Joon-Young Lee , Hailin Jin , Fabian David Caba Heilbron
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/66 ; G06N3/08 ; G06K9/62 ; G06N3/04

Abstract:
Various embodiments describe active learning methods for training temporal action localization models used to localize actions in untrimmed videos. A trainable active learning selection function is used to select unlabeled samples that can improve the temporal action localization model the most. The select unlabeled samples are then annotated and used to retrain the temporal action localization model. In some embodiment, the trainable active learning selection function includes a trainable performance prediction model that maps a video sample and a temporal action localization model to a predicted performance improvement for the temporal action localization model.
Public/Granted literature
- US20190325275A1 ACTIVE LEARNING METHOD FOR TEMPORAL ACTION LOCALIZATION IN UNTRIMMED VIDEOS Public/Granted day:2019-10-24
Information query