mlsanityData to 14 Oct 2026

Videogenic: Identifying Highlight Moments in Videos with Professional Photographs as a Prior

arXiv 2211.12493 ↗First posted 22 Nov 2022cs.CV cs.HC cs.MMcited by 1

Not on the map. Why?

Abstract (arXiv)

This paper investigates the challenge of extracting highlight moments from videos. To perform this task, we need to understand what constitutes a highlight for arbitrary video domains while at the same time being able to scale across different domains. Our key insight is that photographs taken by photographers tend to capture the most remarkable or photogenic moments of an activity. Drawing on this insight, we present Videogenic, a technique capable of creating domain-specific highlight videos for a diverse range of domains. In a human evaluation study (N=50), we show that a high-quality photograph collection combined with CLIP-based retrieval (which uses a neural network with semantic knowledge of images) can serve as an excellent prior for finding video highlights. In a within-subjects expert study (N=12), we demonstrate the usefulness of Videogenic in helping video editors create highlight videos with lighter workload, shorter task completion time, and better usability.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 42 references that are in the map. First posted on arXiv 22 Nov 2022.

Builds on

4 of 42 references.

References · 4

  1. 2019Less is More: Learning Highlight Detection from Video Durationcited by 60
  2. 2016Video2GIF: Automatic Generation of Animated GIFs from Videocited by 41
  3. 2016To Click or Not To Click: Automatic Selection of Beautiful Thumbnails from Videoscited by 34
  4. 2021Learning Personal Style from Few Examplescited by 3

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.