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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 1–50 of 216 papers

TitleStatusHype
TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality AssessmentCode4
The Unreasonable Effectiveness of Deep Features as a Perceptual MetricCode3
VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video GenerationCode3
KVQ: Kwai Video Quality Assessment for Short-form VideosCode2
Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language ModelCode2
FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment SamplingCode2
Enhancing Blind Video Quality Assessment with Rich Quality-aware FeaturesCode2
Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment NetworkCode2
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in VideosCode2
Video Quality Assessment: A Comprehensive SurveyCode2
VQA^2: Visual Question Answering for Video Quality AssessmentCode2
VE-Bench: Subjective-Aligned Benchmark Suite for Text-Driven Video Editing Quality AssessmentCode2
Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical PerspectivesCode2
Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined LevelsCode2
Neighbourhood Representative Sampling for Efficient End-to-end Video Quality AssessmentCode2
Exploring CLIP for Assessing the Look and Feel of ImagesCode2
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and ResultsCode2
Perceptual Quality Assessment of Face Video Compression: A Benchmark and An Effective MethodCode1
Perceptual Quality Assessment of Omnidirectional Images as Moving Camera VideosCode1
Panoramic Vision Transformer for Saliency Detection in 360° VideosCode1
Dual-Branch Network for Portrait Image Quality AssessmentCode1
Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC VideosCode1
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMMCode1
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and ResultsCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and ResultsCode1
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated ContentCode1
MD-VQA: Multi-Dimensional Quality Assessment for UGC Live VideosCode1
AMD-Hummingbird: Towards an Efficient Text-to-Video ModelCode1
Patch-VQ: 'Patching Up' the Video Quality ProblemCode1
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality AssessmentCode1
Modular Blind Video Quality AssessmentCode1
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessmentCode1
Delving Deep into Engagement Prediction of Short VideosCode1
KVQ: Boosting Video Quality Assessment via Saliency-guided Local PerceptionCode1
MUSIQ: Multi-scale Image Quality TransformerCode1
Full Reference Video Quality Assessment for Machine Learning-Based Video CodecsCode1
HIDRO-VQA: High Dynamic Range Oracle for Video Quality AssessmentCode1
A strong baseline for image and video quality assessmentCode1
Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware ConsistencyCode1
CONVIQT: Contrastive Video Quality EstimatorCode1
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain MaximizationCode1
A Deep Learning based No-reference Quality Assessment Model for UGC VideosCode1
FAVER: Blind Quality Prediction of Variable Frame Rate VideosCode1
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video EnhancementCode1
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language GuidanceCode1
Image Quality Assessment: Unifying Structure and Texture SimilarityCode1
ChipQA: No-Reference Video Quality Prediction via Space-Time ChipsCode1
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality ModelsCode1
2BiVQA: Double Bi-LSTM based Video Quality Assessment of UGC VideosCode1
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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