Understanding human behavior and activity facilitates advancement of numerous real-world
applications, and is critical for video analysis. Despite the progress of action recognition …

Weakly-supervised temporal action localization aims to recognize and localize action
segments in untrimmed videos given only video-level action labels for training. Without the …

We target at the task of weakly-supervised action localization (WSAL), where only video-
level action labels are available during model training. Despite the recent progress, existing …

Weakly-supervised temporal action localization (WS-TAL) aims to localize the action
instances and recognize their categories with only video-level labels. Despite great …

Abstract Weakly-supervised Temporal Action Localization (WTAL) attempts to localize the
actions in untrimmed videos using only video-level supervision. Most recent works approach …

With the explosive growth of videos, weakly-supervised temporal action localization (WS-
TAL) task has become a promising research direction in pattern analysis and machine …

Weakly-supervised temporal action localization aims to detect action boundaries in
untrimmed videos with only video-level annotations. Most existing schemes detect temporal …

Weakly-supervised temporal action localization (WTAL) is a practical yet challenging task.
Due to large-scale datasets, most existing methods use a network pretrained in other …

Egocentric videos are often available in the form of uninterrupted, uncurated long videos
capturing the camera wearers' daily life activities. Understanding these videos requires …

Weakly-supervised temporal action localization (WTAL) aims to detect action instances
given only video-level labels. To address the challenge, recent methods commonly employ …