Systems and methods for semantically classifying and normalizing shots in video

One or more non-transitory media storing instructions that, when executed by one or more computing devices, cause performance of:

• within each frame of a sequence of video frames, for each spatial segment of a plurality of spatial segments within the frame, determining likelihoods of the spatial segment corresponding to specific types of contents;
• based on the likelihoods, generating arrangement data for each frame in the sequence, the arrangement data representing a spatial arrangement of the specific types of contents within the frame;
• identifying groups of consecutive video frames, within the sequence, that have similar arrangement data;
• based on the identified groups of consecutive video frames, identifying start times and end times for scenes within a video, the video comprising the video frames.

A system comprising:

• a module, implemented at least partially by computing hardware, configured to, within each frame of a sequence of video frames, for each spatial segment of a plurality of spatial segments within the frame, determining likelihoods of the spatial segment corresponding to specific types of contents;
• a module, implemented at least partially by computing hardware, configured to, based on the likelihoods, generating arrangement data for each frame in the sequence, the arrangement data representing a spatial arrangement of the specific types of contents within the frame;
• a module, implemented at least partially by computing hardware, configured to identify groups of consecutive video frames, within the sequence, that have similar arrangement data;
• a module, implemented at least partially by computing hardware, configured to, based on the identified groups of consecutive video frames, identify start times and end times for scenes within a video, the video comprising the video frames.