Annotated Frame

Annotated frames are crucial for various computer vision tasks, particularly in video analysis, where they serve as training data for models to segment objects, localize actions, or understand complex scenes. Current research focuses on minimizing the number of required annotations through semi-supervised learning and innovative model architectures like memory-based networks and those incorporating attention mechanisms and multi-level consistency strategies. This work is significant because reducing annotation burden accelerates the development of robust and efficient algorithms for applications ranging from video editing and surveillance to behavioral analysis in animals and humans.