Movie Dataset

Movie datasets are crucial for advancing video understanding and related applications, driving research into efficient video analysis, summarization, and content-based recommendation. Current research focuses on developing robust models, often leveraging large language models and deep learning architectures like convolutional neural networks and transformers, to address challenges such as long-video comprehension, multimodal fusion (combining text, visual, and audio data), and bias detection within movie content. These advancements have implications for accessibility (e.g., generating narrations for the visually impaired), improved recommender systems, and a deeper understanding of cinematic storytelling and societal biases reflected in film.