Few Shot Action Recognition

Few-shot Action Recognition is a challenging problem in the field of computer vision, aiming to classify unlabelled query videos using limited samples of action categories from a support set. This task enhances the model's adaptability and generalization performance in new scenarios by reducing the need for annotated data, making it particularly valuable in areas such as video surveillance, human-computer interaction, and intelligent security.