Activity Representation

Activity representation in computer vision focuses on encoding human actions and interactions within video data for improved machine understanding. Current research emphasizes learning hierarchical representations, from atomic actions to complex events, often utilizing graph-based structures or differentiable models to capture temporal relationships and procedural aspects of activities. This work is crucial for advancing applications like video question answering, robotic teleoperation, and assistive technologies by enabling more robust and intuitive interaction with intelligent systems. Furthermore, addressing challenges like imbalanced datasets and online mistake detection is driving the development of more sophisticated and adaptable activity representation methods.