The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …

Recently integrating video foundation models and large language models to build a video
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …

Reinforcement learning algorithms typically struggle in the absence of a dense, well-shaped
reward function. Intrinsically motivated exploration methods address this limitation by …

Human action recognition plays a fundamental role in the design of smart solution for home
environments, particularly in relation to ambient assisted living applications, where the …

Human behavior understanding with unmanned aerial vehicles (UAVs) is of great
significance for a wide range of applications, which simultaneously brings an urgent …

In a real-world scenario, human actions are typically out of the distribution from training data,
which requires a model to both recognize the known actions and reject the unknown …

Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …

We focus on the problem of predicting future states of entities in complex, real-world driving
scenarios. Previous research has approached this problem via low-level signals to predict …

Over the last few years there has been rapid research growth into eXplainable Artificial
Intelligence (XAI) and the closely aligned Interpretable Machine Learning (IML). Drivers for …