Traditional video action detectors typically adopt the two-stage pipeline, where a person
detector is first employed to yield actor boxes and then 3D RoIAlign is used to extract actor …

Spatio-temporal action detection (STAD) aims to classify the actions present in a video and
localize them in space and time. It has become a particularly active area of research in …

This paper presents a novel spatiotemporal transformer network that introduces several
original components to detect actions in untrimmed videos. First, the multi-feature selective …

Despite being extensively used in numerous uses, precise and effective human activity
identification continues to be an interesting research issue in the area of vision for …

Spatial and temporal action detection aims to precisely locate actions while predicting their
respective categories. The existing solution, TubeR (Zhao et al., 2022), is designed to …

Intelligent vehicle systems require a deep understanding of the interplay between road
conditions, surrounding entities, and the ego vehicle's driving behavior for safe and efficient …

This study introduces an innovative Temporal Action Detection (TAD) model that is
distinguished by its lightweight structure and capability for end-to-end training, delivering …

Soccer analytics rely on two data sources: the player positions on the pitch and the
sequences of events they perform. With around 2000 ball events per game, their precise and …

In this paper, we propose a method that extends the query-based object detection model,
DETR, to spatio-temporal action detection, which requires maintaining temporal consistency …

Spatio-temporal action detection (STAD) is a task receiving widespread attention and has
numerous application scenarios, such as video surveillance and smart education. Current …