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 …

Abstract Weakly Supervised Temporal Action Localization (WSTAL) aims to jointly localize
and classify action segments in untrimmed videos with only video level annotations. To …

Weakly-supervised temporal action localization (WTAL) aims to localize and classify action
instances in untrimmed videos with only video-level labels available. Despite the …

Point-supervised Temporal Action Localization (PSTAL) is an emerging research direction
for label-efficient learning. However, current methods mainly focus on optimizing the network …

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

In this paper, we address the problem of weakly supervised Audio-Visual Video Parsing
(AVVP), where the goal is to temporally localize events that are audible or visible and …

Weakly-supervised temporal action localization (WTAL) is a problem learning an action
localization model with only video-level labels available. In recent years, many WTAL …

Recently, temporal action localization (TAL) methods, especially the weakly-supervised and
unsupervised ones, have become a hot research topic. Existing unsupervised methods …

Localizing human actions in videos has attracted extensive attention from industry and
academia. Few-Shot Temporal Action Localization (FS-TAL) aims to detect human actions in …

Weakly supervised temporal action localization aims to locate the temporal boundaries of
action instances in untrimmed videos using video-level labels and assign them the …