  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.
