Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …

We present SkeleTR, a new framework for skeleton-based action recognition. In contrast to
prior work, which focuses mainly on controlled environments, we target in-the-wild scenarios …

Human-centric video frame interpolation has great potential for enhancing entertainment
experiences and finding commercial applications in sports analysis industry eg synthesizing …

Learning spatial and temporal relations among people plays an important role in
recognizing group activity. Recently, transformer-based methods have become popular …

Modeling actor interaction relations is crucial for group activity recognition. Previous
approaches often adopt a fixed paradigm that involves calculating an affinity matrix to model …

Social group activity recognition is a challenging task extended from group activity
recognition, where social groups must be recognized with their activities and group …

Group activity recognition aims at understanding the overall activity involved multi-person
interaction with each other as a whole in the complex variations in both spatial and temporal …

Abstract This paper proposes Group Activity Feature (GAF) learning in which features of
multi-person activity are learned as a compact latent vector. Unlike prior work in which the …

The study of complex human interactions and group activities has become a focal point in
human-centric computer vision. However progress in related tasks is often hindered by the …

Despite significant progress in video question answering (VideoQA), existing methods fall
short of questions that require causal/temporal reasoning across frames. This can be …