The document discusses style transfer techniques for both static images and videos. It explains how convolutional neural networks can be used to extract content and style features from images to generate an output image that matches the content of one image but has the visual style of another. For videos, additional temporal constraints are needed to ensure stylistic consistency between adjacent frames. Recent advances indicate that real-time video style transfer on streaming data may soon be possible on mobile devices through apps from companies like Facebook and Google.