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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
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
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and ResultsCode1
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
AMD-Hummingbird: Towards an Efficient Text-to-Video ModelCode1
KVQ: Boosting Video Quality Assessment via Saliency-guided Local PerceptionCode1
Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language ModelCode2
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
Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware ConsistencyCode1
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
VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video GenerationCode3
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
Video Quality Assessment: A Comprehensive SurveyCode2
Subjective and Objective Quality Assessment Methods of Stereoscopic Videos with Visibility Affecting Distortions—0
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMMCode1
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric—0
VQA^2: Visual Question Answering for Video Quality AssessmentCode2
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
Delving Deep into Engagement Prediction of Short VideosCode1
Advancing Video Quality Assessment for AIGC—0
Revisiting Video Quality Assessment from the Perspective of GeneralizationCode0
LMM-VQA: Advancing Video Quality Assessment with Large Multimodal ModelsCode0
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and ResultsCode1
VE-Bench: Subjective-Aligned Benchmark Suite for Text-Driven Video Editing Quality AssessmentCode2
BVI-UGC: A Video Quality Database for User-Generated Content Transcoding—0
Subjective and Objective Quality Assessment of Rendered Human Avatar Videos in Virtual Reality—0
Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified ModelCode0
Highly Efficient No-reference 4K Video Quality Assessment with Full-Pixel Covering Sampling and Training Strategy—0
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in VideosCode2
ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality AssessmentCode1
CLIPVQA:Video Quality Assessment via CLIPCode0
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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