Video Based Model

Video-based models aim to analyze and understand information contained within video sequences, going beyond the capabilities of image-only approaches by leveraging temporal context. Current research focuses on improving efficiency (e.g., through knowledge distillation and reduced data requirements), enhancing accuracy in tasks like action recognition, object segmentation, and lesion detection, and addressing challenges related to computational cost and data annotation. These advancements are significant for various applications, including medical diagnosis, autonomous driving, and virtual reality, where real-time processing and accurate interpretation of dynamic visual information are crucial.