Papers › No-Reference Video Quality Assessment Using Space-Time Chips

No-Reference Video Quality Assessment Using Space-Time Chips

23 Aug 2020arXiv:2008.00031archive 2025-07-28

We propose a new prototype model for no-reference video quality assessment (VQA) based on the natural statistics of space-time chips of videos. Space-time chips (ST-chips) are a new, quality-aware feature space which we define as space-time localized cuts of video data in directions that are determined by the local motion flow. We use parametrized distribution fits to the bandpass histograms of space-time chips to characterize quality, and show that the parameters from these models are affected by distortion and can hence be used to objectively predict the quality of videos. Our prototype method, which we call ChipQA-0, is agnostic to the types of distortion affecting the video, and is based on identifying and quantifying deviations from the expected statistics of natural, undistorted ST-chips in order to predict video quality. We train and test our resulting model on several large VQA databases and show that our model achieves high correlation against human judgments of video quality and is competitive with state-of-the-art models.

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Video Quality AssessmentVisual Question Answering (VQA)

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Video Quality Assessment LIVE Livestream ChipQA-0 SRCC 0.7513 #2 of 4 Archive leaderboard report
Video Quality Assessment LIVE-ETRI ChipQA-0 SRCC 0.4028 #5 of 7 Archive leaderboard report

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