A Subjective and Objective Study of Space-Time Subsampled Video Quality
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Abstract (arXiv)
Video dimensions are continuously increasing to provide more realistic and immersive experiences to global streaming and social media viewers. However, increments in video parameters such as spatial resolution and frame rate are inevitably associated with larger data volumes. Transmitting increasingly voluminous videos through limited bandwidth networks in a perceptually optimal way is a current challenge affecting billions of viewers. One recent practice adopted by video service providers is space-time resolution adaptation in conjunction with video compression. Consequently, it is important to understand how different levels of space-time subsampling and compression affect the perceptual quality of videos. Towards making progress in this direction, we constructed a large new resource, called the ETRI-LIVE Space-Time Subsampled Video Quality (ETRI-LIVE STSVQ) database, containing 437 videos generated by applying various levels of combined space-time subsampling and video compression on 15 diverse video contents. We also conducted a large-scale human study on the new dataset, collecting about 15,000 subjective judgments of video quality. We provide a rate-distortion analysis of the collected subjective scores, enabling us to investigate the perceptual impact of space-time subsampling at different bit rates. We also evaluated and compared the performance of leading video quality models on the new database.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jan 2021.
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Citing papers per year: 2021: 1; 2022: 4; 2023: 4; 2024: 3; 2025: 2.
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- 2023Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Modelscited by 38
- 2024Modular Blind Video Quality Assessmentcited by 23
- 2021ChipQA: No-Reference Video Quality Prediction via Space-Time Chipscited by 22
- 2022CONVIQT: Contrastive Video Quality Estimatorcited by 19
- 2024Enhancing Blind Video Quality Assessment with Rich Quality-aware Featurescited by 19
- 2024Video Quality Assessment: A Comprehensive Surveycited by 15
- 2022FAVER: Blind Quality Prediction of Variable Frame Rate Videoscited by 10
- 2022BVI-VFI: A Video Quality Database for Video Frame Interpolationcited by 7
- 2023HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videoscited by 7
- 2023Making Video Quality Assessment Models Robust to Bit Depthcited by 6
- 2023HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videoscited by 4
- 2025Engagement Prediction of Short Videos with Large Multimodal Modelscited by 4
2 more
- 2025Engagement Prediction of Short Videos with Large Multimodal Models4 Aug 2025
- 2025CGVQM+D: Computer Graphics Video Quality Metric and Dataset13 Jun 2025
- 2024Video Quality Assessment: A Comprehensive Survey4 Dec 2024
- 2024Enhancing Blind Video Quality Assessment with Rich Quality-aware Features14 May 2024
- 2024Modular Blind Video Quality Assessment29 Feb 2024
- 2023Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models26 Jul 2023
- 2023HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos25 Apr 2023
- 2023HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videos25 Apr 2023
- 2023Making Video Quality Assessment Models Robust to Bit Depth25 Apr 2023
- 2022BVI-VFI: A Video Quality Database for Video Frame Interpolation3 Oct 2022
- 2022CONVIQT: Contrastive Video Quality Estimator29 Jun 2022
- 2022Making Video Quality Assessment Models Sensitive to Frame Rate Distortions21 May 2022
2 more
- 2023Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Modelscited by 38
- 2024Modular Blind Video Quality Assessmentcited by 23
- 2021ChipQA: No-Reference Video Quality Prediction via Space-Time Chipscited by 22
- 2022CONVIQT: Contrastive Video Quality Estimatorcited by 19
- 2024Enhancing Blind Video Quality Assessment with Rich Quality-aware Featurescited by 19
- 2024Video Quality Assessment: A Comprehensive Surveycited by 15
- 2022FAVER: Blind Quality Prediction of Variable Frame Rate Videoscited by 10
- 2022BVI-VFI: A Video Quality Database for Video Frame Interpolationcited by 7
- 2023HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videoscited by 7
- 2023Making Video Quality Assessment Models Robust to Bit Depthcited by 6
- 2023HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videoscited by 4
- 2022Making Video Quality Assessment Models Sensitive to Frame Rate Distortionscited by 2
12 most cited of 13 All 13 (JSON)
- 2025CGVQM+D: Computer Graphics Video Quality Metric and Dataset13 Jun 2025
- 2024Video Quality Assessment: A Comprehensive Survey4 Dec 2024
- 2024Enhancing Blind Video Quality Assessment with Rich Quality-aware Features14 May 2024
- 2024Modular Blind Video Quality Assessment29 Feb 2024
- 2023Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models26 Jul 2023
- 2023HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos25 Apr 2023
- 2023HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videos25 Apr 2023
- 2023Making Video Quality Assessment Models Robust to Bit Depth25 Apr 2023
- 2022BVI-VFI: A Video Quality Database for Video Frame Interpolation3 Oct 2022
- 2022CONVIQT: Contrastive Video Quality Estimator29 Jun 2022
- 2022Making Video Quality Assessment Models Sensitive to Frame Rate Distortions21 May 2022
- 2022FAVER: Blind Quality Prediction of Variable Frame Rate Videos5 Jan 2022
12 newest of 13 All 13 (JSON)