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Video Quality Assessment

Video Quality Assessment is a computer vision task aiming to mimic video-based human subjective perception. The goal is to produce a mos score, where higher score indicates better perceptual quality. Some well-known benchmarks for this task are KoNViD-1k, LIVE-VQC, YouTube-UGC and LSVQ. SROCC/PLCC/RMSE are usually used to evaluate the performance of different models.

Papers

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Showing 51–100 of 216 papers

TitleStatusHype
A crowdsourcing approach to video quality assessmentCode1
FAVER: Blind Quality Prediction of Variable Frame Rate VideosCode1
A strong baseline for image and video quality assessmentCode1
Image Quality Assessment using Contrastive LearningCode1
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
ChipQA: No-Reference Video Quality Prediction via Space-Time ChipsCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
MUSIQ: Multi-scale Image Quality TransformerCode1
Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC VideosCode1
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated ContentCode1
Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality AssessmentCode1
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality AssessmentCode1
Patch-VQ: 'Patching Up' the Video Quality ProblemCode1
Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets TrainingCode1
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality PredictionCode1
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated ContentCode1
Perceptual Quality Assessment of Omnidirectional Images as Moving Camera VideosCode1
Image Quality Assessment: Unifying Structure and Texture SimilarityCode1
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain MaximizationCode1
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentCode1
The 2018 PIRM Challenge on Perceptual Image Super-resolutionCode1
Towards Deep Learning Models Resistant to Adversarial AttacksCode1
Bridging Video Quality Scoring and Justification via Large Multimodal Models—0
EyeSim-VQA: A Free-Energy-Guided Eye Simulation Framework for Video Quality Assessment—0
TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs—0
NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and ResultsCode0
CP-LLM: Context and Pixel Aware Large Language Model for Video Quality Assessment—0
Semantically-Aware Game Image Quality Assessment—0
Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-SupervisionCode0
DiffVQA: Video Quality Assessment Using Diffusion Feature Extractor—0
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study—0
DVLTA-VQA: Decoupled Vision-Language Modeling with Text-Guided Adaptation for Blind Video Quality Assessment—0
FVQ: A Large-Scale Dataset and A LMM-based Method for Face Video Quality AssessmentCode0
Adaptive Score Alignment Learning for Continual Perceptual Quality Assessment of 360-Degree Videos in Virtual RealityCode0
InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model—0
A Multi-annotated and Multi-modal Dataset for Wide-angle Video Quality Assessment—0
Cross-Modal Transferable Image-to-Video Attack on Video Quality MetricsCode0
Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling—0
Multilevel Semantic-Aware Model for AI-Generated Video Quality Assessment—0
ESVQA: Perceptual Quality Assessment of Egocentric Spatial Videos—0
FineVQ: Fine-Grained User Generated Content Video Quality Assessment—0
TINQ: Temporal Inconsistency Guided Blind Video Quality AssessmentCode0
An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM—0
OnlineVPO: Align Video Diffusion Model with Online Video-Centric Preference Optimization—0
Subjective and Objective Quality Assessment Methods of Stereoscopic Videos with Visibility Affecting Distortions—0
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric—0
Deep Priors for Video Quality Prediction—0
Latent Image and Video Resolution Prediction using Convolutional Neural Networks—0
Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities—0
Secure Video Quality Assessment Resisting Adversarial Attacks—0
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All datasetsMSU SR-QA DatasetKoNViD-1kMSU NR VQA DatabaseLIVE-VQCMSU FR VQA DatabaseYouTube-UGCLIVE-FB LSVQLIVE-ETRILIVE LivestreamLIVE-YT-HFR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PieAPPSROCC0.75—Unverified
2Q-Align (IQA)SROCC0.75—Unverified
3Q-Align (VQA)SROCC0.72—Unverified
4PaQ-2-PiQSROCC0.71—Unverified
5DBCNNSROCC0.69—Unverified
6MUSIQ trained on PaQ-2-PiQSROCC0.68—Unverified
7Ma-MetricSROCC0.67—Unverified
8MANIQASROCC0.67—Unverified
9ClipIQA+ ResNet50SROCC0.66—Unverified
10MUSIQ trained on SPAQSROCC0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1DOVER (end-to-end)PLCC0.91—Unverified
2FasterVQA (fine-tuned)PLCC0.9—Unverified
3DOVER (head-only)PLCC0.89—Unverified
4FAST-VQA (finetuned on KonViD-1k)PLCC0.89—Unverified
5ReLaX-VQA (finetuned on KoNViD-1k)PLCC0.87—Unverified
6SimpleVQAPLCC0.86—Unverified
7DisCoVQAPLCC0.86—Unverified
8HVS-5MPLCC0.86—Unverified
9FAST-VQA (trained on LSVQ only)PLCC0.86—Unverified
10CONVIQTPLCC0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1MDTVSFASRCC0.93—Unverified
2DBCNNSRCC0.92—Unverified
3UNIQUESRCC0.91—Unverified
4LISRCC0.91—Unverified
5LINEARITYSRCC0.91—Unverified
6VSFASRCC0.9—Unverified
7MUSIQSRCC0.9—Unverified
8DOVERSRCC0.89—Unverified
9SPAQ MT-SSRCC0.88—Unverified
10SPAQ BLSRCC0.88—Unverified
#ModelMetricClaimedVerifiedStatus
1ReLaX-VQA (finetuned on LIVE-VQC)PLCC0.89—Unverified
2DOVER (end-to-end)PLCC0.87—Unverified
3DOVER (head-only)PLCC0.86—Unverified
4FAST-VQA (finetuned on LIVE-VQC)PLCC0.86—Unverified
5FasterVQA (fine-tuned)PLCC0.86—Unverified
6FAST-VQA (trained on LSVQ only)PLCC0.84—Unverified
7DisCoVQAPLCC0.84—Unverified
8HVS-5MPLCC0.84—Unverified
9BVQA-2022PLCC0.84—Unverified
102BiVQAPLCC0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1VMAF Y (v061)SRCC0.94—Unverified
2VMAF Y (v062)SRCC0.94—Unverified
3VMAF Y (v063)SRCC0.94—Unverified
4AHIQSRCC0.94—Unverified
5VMAF Y (v061_neg)SRCC0.91—Unverified
6VIFpSRCC0.91—Unverified
7VSISRCC0.91—Unverified
8MS-SSIMSRCC0.9—Unverified
9SR-SIMSRCC0.9—Unverified
10FSIMSRCC0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1DOVER (end-to-end)PLCC0.87—Unverified
2ReLaX-VQA (finetuned on YouTube-UGC)PLCC0.87—Unverified
3DOVER (head-only)PLCC0.86—Unverified
4FasterVQA (fine-tuned)PLCC0.86—Unverified
5SimpleVQAPLCC0.86—Unverified
6FAST-VQA (finetuned on YouTube-UGC)PLCC0.85—Unverified
7HVS-5MPLCC0.85—Unverified
8ReLaX-VQA (trained on LSVQ only)PLCC0.84—Unverified
9CONVIQTPLCC0.82—Unverified
10ReLaX-VQAPLCC0.82—Unverified
#ModelMetricClaimedVerifiedStatus
1OneAlign + FAST-VQAPLCC0.9—Unverified
2DOVERPLCC0.89—Unverified
3OneAlignPLCC0.89—Unverified
4FAST-VQAPLCC0.88—Unverified
5FasterVQAPLCC0.87—Unverified
6HVS-5MPLCC0.87—Unverified
7SimpleVQAPLCC0.86—Unverified
8BVQA-2022PLCC0.85—Unverified
9DisCoVQAPLCC0.85—Unverified
10PVQPLCC0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1CONVIQTSRCC0.94—Unverified
2CONTRIQUESRCC0.93—Unverified
3ChipQASRCC0.63—Unverified
4VBLIINDSSRCC0.48—Unverified
5ChipQA-0SRCC0.4—Unverified
6BRISQUESRCC0.27—Unverified
7TLVQMSRCC0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1ChipQASRCC0.76—Unverified
2ChipQA-0SRCC0.75—Unverified
3TLVQMSRCC0.75—Unverified
4RAPIQUESRCC0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1ST-GREEDSRCC0.88—Unverified
2GREED-VMAFSRCC0.87—Unverified
3GSTISRCC0.81—Unverified