Video Summarization by Learning from Unpaired Data

Understand

We consider the problem of video summarization.

• Given an input raw video, the goal is to select a small subset of key frames from the input video to create a shorter summary video that best describes the content of the original video.
• Most of the current state-of-the-art video summarization approaches use supervised learning and require labeled training data.
• Each training instance consists of a raw input video and its ground truth summary video curated by human annotators.