Heatmap regression has become the most prevalent choice for nowadays human pose
estimation methods. The ground-truth heatmaps are usually constructed by covering all …

Effectively tackling the problem of temporal action localization (TAL) necessitates a visual
representation that jointly pursues two confounding goals, ie, fine-grained discrimination for …

Human action anticipation aims at predicting what people will do in the future based on past
observations. In this paper we introduce Uncertainty-aware Action Decoupling Transformer …

Joint video-language learning has received increasing attention in recent years. However,
existing works mainly focus on single or multiple trimmed video clips (events), which makes …

In this paper, we introduce ASTRA, a Transformer-based model designed for the task of
Action Spotting in soccer matches. ASTRA addresses several challenges inherent in the …

Effectively tackling the problem of temporal action localization (TAL) necessitates a visual
representation that jointly pursues two confounding goals, ie, fine-grained discrimination for …

Weakly-supervised temporal action localization (WTAL) is a challenging task in
understanding untrimmed videos, in which no frame-wise annotation is provided during …

We propose a Temporal Voting Network (TVNet) for action localization in untrimmed videos.
This incorporates a novel Voting Evidence Module to locate temporal boundaries, more …

Temporal action detection is a crucial aspect of video understanding. It aims to classify the
action as well as locate the start and end boundaries of the action in the untrimmed videos …

The Online Detection of Action Start (ODAS) has attracted the attention of researchers
because of its practical applications in areas such as security and emergency response …