Abstract: This disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that can detect scene types across various portions of media content and display collections that organize segments (or portions) of media content (e.g., videos or images) according to the detected scene types for the media content files. For example, the disclosed systems can automatically identify content segments of media content that belong to one or more identified scene types and display the content segments organized by the different scene types. In order to determine the scene types for the content segments of the media content files, the disclosed systems can utilize machine learning that determines relevancies between data of the media content files and the scene types. Furthermore, the disclosed systems can display, within a GUI, the groupings of media content segments organized by the different scene types.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing synthetic visualizations representative of content collections within a content management system. In some cases, the disclosed systems generate a synthetic visualization based on content features that indicate relevance of content items with respect to a user account to emphasize more relevant content items within the synthetic visualization and/or to represent descriptive content attributes of the content items. For example, the disclosed systems can generate a synthetic phrase that represents a content collection and can further generate a synthetic visualization from the synthetic phrase utilizing a synthetic visualization machine learning model.