Multimodal Large Language Models (MLLMs) are advancing the ability to reason about
complex sports scenarios by integrating textual and visual information. To comprehensively …

Action Quality Assessment (AQA) quantitatively evaluates the quality of human actions,
providing automated assessments that reduce biases in human judgment. Its applications …

Multi-object tracking (MOT) aims to estimate the bounding boxes and ID labels of objects in
videos. The challenging issue in this task is to alleviate competitive learning between the …

Our world is full of varied actions and moves across specialized domains that we, as
humans, strive to identify and understand. Within any single domain, actions can often …

Zero-shot skeleton action recognition is a non-trivial task that requires robust unseen
generalization with prior knowledge from only seen classes and shared semantics. Existing …

We introduce an open dataset for video event spotting focused on fast-paced events in
shadowboxing videos captured at high frame rates. The dataset features accurate frame …