mlsanityData to 7 Oct 2026

Patch-VQ: 'Patching Up' the Video Quality Problem

arXiv 2011.13544 ↗First posted 27 Nov 2020cs.CVcited by 147

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Abstract (arXiv)

No-reference (NR) perceptual video quality assessment (VQA) is a complex, unsolved, and important problem to social and streaming media applications. Efficient and accurate video quality predictors are needed to monitor and guide the processing of billions of shared, often imperfect, user-generated content (UGC). Unfortunately, current NR models are limited in their prediction capabilities on real-world, "in-the-wild" UGC video data. To advance progress on this problem, we created the largest (by far) subjective video quality dataset, containing 39, 000 realworld distorted videos and 117, 000 space-time localized video patches ('v-patches'), and 5.5M human perceptual quality annotations. Using this, we created two unique NR-VQA models: (a) a local-to-global region-based NR VQA architecture (called PVQ) that learns to predict global video quality and achieves state-of-the-art performance on 3 UGC datasets, and (b) a first-of-a-kind space-time video quality mapping engine (called PVQ Mapper) that helps localize and visualize perceptual distortions in space and time. We will make the new database and prediction models available immediately following the review process.

Key facts. Cited by 147 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Nov 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 16; 2023: 25; 2024: 42; 2025: 37; 2026: 23.

147 papers.

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  1. 2023Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levelscited by 489
  2. 2022Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectivescited by 314
  3. 2023Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Visioncited by 247
  4. 2022FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Samplingcited by 179
  5. 2022A Deep Learning based No-reference Quality Assessment Model for UGC Videoscited by 128
  6. 2021RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Contentcited by 100
  7. 2021Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion Perceptioncited by 97
  8. 2022Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessmentcited by 50
  9. 2024Towards A Better Metric for Text-to-Video Generationcited by 50
  10. 2023MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videoscited by 46
  11. 2023Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approachcited by 45
  12. 2022DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessmentcited by 41
38 more
  1. 2024Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMscited by 39
  2. 2023Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Modelscited by 38
  3. 2024KVQ: Kwai Video Quality Assessment for Short-form Videoscited by 38
  4. 2024GAIA: Rethinking Action Quality Assessment for AI-Generated Videoscited by 30
  5. 2024NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Resultscited by 29
  6. 2024LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Modelscited by 28
  7. 2024FineVQ: Fine-Grained User Generated Content Video Quality Assessmentcited by 28
  8. 2022Video compression dataset and benchmark of learning-based video-quality metricscited by 27
  9. 2023Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluationcited by 27
  10. 2024Quality Assessment in the Era of Large Models: A Surveycited by 26
  11. 2025VQ-Insight: Teaching VLMs for AI-Generated Video Quality Understanding via Progressive Visual Reinforcement Learningcited by 26
  12. 2022Exploring the Effectiveness of Video Perceptual Representation in Blind Video Quality Assessmentcited by 25
  13. 2023Exploring Opinion-unaware Video Quality Assessment with Semantic Affinity Criterioncited by 23
  14. 2024Modular Blind Video Quality Assessmentcited by 23
  15. 2023Subjective and Objective Quality Assessment for in-the-Wild Computer Graphics Imagescited by 21
  16. 2023Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessmentcited by 21
  17. 2023Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessmentcited by 20
  18. 2024NTIRE 2024 Quality Assessment of AI-Generated Content Challengecited by 20
  19. 2022CONVIQT: Contrastive Video Quality Estimatorcited by 19
  20. 2024Enhancing Blind Video Quality Assessment with Rich Quality-aware Featurescited by 19
  21. 2023Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessmentcited by 18
  22. 2024PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wildcited by 17
  23. 2023Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessmentcited by 16
  24. 2021StarVQA: Space-Time Attention for Video Quality Assessmentcited by 15
  25. 2021A strong baseline for image and video quality assessmentcited by 15
  26. 2024VQA2: Visual Question Answering for Video Quality Assessmentcited by 15
  27. 2024Video Quality Assessment: A Comprehensive Surveycited by 15
  28. 2022Subjective and Objective Analysis of Streamed Gaming Videoscited by 14
  29. 2023Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective Methodcited by 14
  30. 2025NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Resultscited by 14
  31. 2024Scaling and Masking: A New Paradigm of Data Sampling for Image and Video Quality Assessmentcited by 13
  32. 2024Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution Gapcited by 13
  33. 2024Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Modelcited by 13
  34. 2025FVQ: A Large-Scale Dataset and an LMM-based Method for Face Video Quality Assessmentcited by 13
  35. 2023Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancementcited by 12
  36. 2023Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attackscited by 12
  37. 2023CLiF-VQA: Enhancing Video Quality Assessment by Incorporating High-Level Semantic Information related to Human Feelingscited by 11
  38. 2024CLIPVQA:Video Quality Assessment via CLIPcited by 11

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