DVL2021: An ultra high definition video dataset for perceptual quality study

Xing, Fengchuang; Wang, Yuan‐Gen; Wang, Hanpin; He, Jun; Yuan, Juntao

doi:10.1016/j.jvcir.2021.103374

Cited by 8 publications

(1 citation statement)

References 23 publications

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“…In Table 1, a selection of commonly use datasets for video compression research is listed along with some of their basic features. Some of these datasets consist of pristine sequences [those that include raw (uncompressed) video sequences in the dataset] and others of UGC content [no raw sequences available as in KonViD-1K (Hosu et al (2017)], YouTube-UGC [Wang et al (2019)], DVL 2021 [Xing et al (2022)]. Most of the existing datasets with pristine content, only include encoded sequences with one codec, usually H.264 {e.g., VQEGHD3 [Video Quality Experts Group (2010)], LIVE [Seshadrinathan et al (2010)], NFLX-P and VMAF+ [Li et al (2016)]} or HEVC {e.g., BVI-HD [Zhang et al (2018)], BVI-Texture [Papadopoulos et al (2015)], BVI-SynTex [Katsenou A. V. et al (2021)]}.…”

Section: Datasets For Video Compression Purposesmentioning

confidence: 99%

BVI-CC: A Dataset for Research on Video Compression and Quality Assessment

Katsenou

Zhang

Afonso

et al. 2022

Front. Signal Process.

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The video technology scenery has been very vivid over the past years, with novel video coding technologies introduced that promise improved compression performance over state-of-the-art technologies. Despite the fact that a lot of video datasets are available, representative content of the wide parameter space along with subjective evaluations of variations of encoded content from an unpartial end is required. In response to this requirement, this paper features a dataset, the BVI-CC. Three video codecs were deployed to create the variations of the encoded sequences: High Efficiency Video Coding Test Model (HM), AOMedia Video 1 (AV1), and Versatile Video Coding Test Model (VTM). Nine source video sequences were carefully selected to offer both diversity and representativeness in the spatio-temporal domain. Different spatial resolution versions of the sequences were created and encoded by all three codecs at pre-defined target bit rates. The compression efficiency of the codecs was evaluated with commonly used objective quality metrics, and the subjective quality of their reconstructed content was also evaluated through psychophysical experiments. Additionally, an adaptive bit rate (convex hull rate-distortion optimization across spatial resolutions) test case was assessed using both objective and subjective evaluations. Finally, the computational complexities of the tested codecs were examined. All data have been made publicly available as part of the dataset, which can be used for coding performance evaluation and video quality metric development.

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