Scene Detection

Scene detection in video aims to automatically segment videos into semantically meaningful units, such as scenes or shots, facilitating various downstream tasks like video summarization and content analysis. Current research focuses on improving the accuracy and efficiency of scene detection using deep learning models, including transformers and state-space models, often incorporating techniques like semi-supervised learning and multi-modal data fusion (e.g., combining visual and textual information). These advancements are crucial for applications ranging from video indexing and retrieval to automated content generation and analysis of historical visual archives. The development of more robust and efficient scene detection methods is driving progress in numerous fields, including computer vision, multimedia processing, and information retrieval.