arXiv:2605.20838v1 Announce Type: cross Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-generated short-form videos have rarely been studied. This paper presents USV, the User-generated Short-form Video dataset for high-level semantic video understanding. The dataset contains around 224K videos collected from UGC platforms by label queries without extra manual verification and trimming. Although video understanding has achieved plausible improvement these years, most works focus on i
The proliferation of user-generated short-form video content has created a new frontier for AI research in video understanding, necessitating specialized datasets.
This new dataset addresses a significant gap in high-level semantic video understanding for a rapidly growing and structurally important content format.
The availability of a large-scale, user-generated short-form video dataset will allow for more accurate and nuanced AI models tailored to this pervasive content type.
- · AI researchers
- · social media platforms
- · content creation tools
- · marketing and advertising
- · traditional video dataset providers
Improved AI models for short-form video analysis and content moderation.
More sophisticated, personalized user experiences on platforms heavily featuring short-form video content.
Potential for new AI-powered applications that generate, edit, or summarize short-form video at scale, impacting media consumption habits.
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Read at arXiv cs.AI