SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 216 papers

TitleStatusHype
Priorformer: A UGC-VQA Method with content and distortion priors—0
VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation—0
MVAD: A Multiple Visual Artifact Detector for Video Streaming—0
PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild—0
Enhancing Blind Video Quality Assessment with Rich Quality-aware FeaturesCode2
Dual-Branch Network for Portrait Image Quality AssessmentCode1
RMT-BVQA: Recurrent Memory Transformer-based Blind Video Quality Assessment for Enhanced Video Content—0
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language GuidanceCode1
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge—0
AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and ResultsCode0
PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition—0
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and ResultsCode2
THQA: A Perceptual Quality Assessment Database for Talking HeadsCode1
Study of the effect of Sharpness on Blind Video Quality Assessment—0
Learned Scanpaths Aid Blind Panoramic Video Quality AssessmentCode0
Subjective-Aligned Dataset and Metric for Text-to-Video Quality AssessmentCode1
Modular Blind Video Quality AssessmentCode1
KVQ: Kwai Video Quality Assessment for Short-form VideosCode2
Perceptual Video Quality Assessment: A Survey—0
Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy—0
Scaling and Masking: A New Paradigm of Data Sampling for Image and Video Quality AssessmentCode1
Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined LevelsCode2
Knowledge Guided Semi-Supervised Learning for Quality Assessment of User Generated VideosCode0
Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models—0
Full-reference Video Quality Assessment for User Generated Content Transcoding—0
RankDVQA-mini: Knowledge Distillation-Driven Deep Video Quality Assessment—0
HIDRO-VQA: High Dynamic Range Oracle for Video Quality AssessmentCode1
CLiF-VQA: Enhancing Video Quality Assessment by Incorporating High-Level Semantic Information related to Human Feelings—0
Geometry-Aware Video Quality Assessment for Dynamic Digital Human—0
Video Quality Assessment and Coding Complexity of the Versatile Video Coding Standard—0
Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial AttacksCode1
Full Reference Video Quality Assessment for Machine Learning-Based Video CodecsCode1
UGC Quality Assessment: Exploring the Impact of Saliency in Deep Feature-Based Quality AssessmentCode0
StableVQA: A Deep No-Reference Quality Assessment Model for Video StabilityCode1
TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality AssessmentCode4
Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment—0
Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessment—0
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality ModelsCode1
NTIRE 2023 Quality Assessment of Video Enhancement Challenge—0
Subjective and Objective Audio-Visual Quality Assessment for User Generated ContentCode0
StarVQA+: Co-training Space-Time Attention for Video Quality AssessmentCode0
Blind Video Quality Assessment at the Edge—0
Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos—0
Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted ApproachCode1
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video EnhancementCode1
SB-VQA: A Stack-Based Video Quality Assessment Framework for Video Enhancement—0
SR+Codec: a Benchmark of Super-Resolution for Video Compression Bitrate ReductionCode0
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming ContentCode0
Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality AssessmentCode1
HDR-VDP-3: A multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content—0
Show:102550
← PrevPage 2 of 5Next →
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