Youtube SFV+HDR Quality Dataset
The popularity of Short form videos (SFV) has grown dramatically in the past few years, and has become a phenomenal video category with billions of viewers. Meanwhile, High Dynamic Range (HDR) as an advanced feature also becomes more and more popular on video sharing platforms. As a hot topic with huge impact, SFV and HDR bring new questions to video quality research: 1) is SFV+HDR quality assessment significantly different from traditional User Generated Content (UGC) quality assessment? 2) do objective quality metrics designed for traditional UGC still work well for SFV+HDR? To answer the above questions, we created the first large scale SFV+HDR dataset with reliable subjective quality scores, covering 10 popular content categories. Further, we also introduce a general sampling framework to maximize the representativeness of the dataset. We provided a comprehensive analysis of subjective quality scores for Short form SDR and HDR videos, and discuss the reliability of state-of-the-art UGC quality metrics and potential improvements.
Authors
- Balu Adsumilli (ORCID: https://orcid.org/0000-0002-5187-6331)
- Joong Gon Yim
- Neil Birkbeck
- Yilin Wang (ORCID: https://orcid.org/0000-0003-4031-8753)
Institutions
- Google (United States) (US)
Publication Details
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/icip51287.2024.10647927
- Citations
- 3
- Primary Topic
- Image Enhancement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.75