USV: Towards Understanding the User-generated Short-form Videos
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 instance-level recognition, which is not sufficient for learning the representation of the high-level semantic information of videos. Therefore, we ...
| Authors | Haoyue Cheng, Su Xu, Liwei Jin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 May 2026 |
| Last updated at source | 20 May 2026 |
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