StoryFrames is a human-annotated dataset created to enhance a model's capability of understanding and reasoning over sequences of images.
It is specifically designed for tasks like generating a description for the next scene in a story based on previous visual and textual information.
The dataset repurposes the StoryBench dataset, a video dataset originally designed to predict future frames of a video.
StoryFrames subsamples frames from those videos and pairs… See the full description on the dataset page:
https://huggingface.co/datasets/ingoziegler/StoryFrames.
