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

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Showing 151–200 of 216 papers

TitleStatusHype
DCVQE: A Hierarchical Transformer for Video Quality Assessment—0
HVS Revisited: A Comprehensive Video Quality Assessment Framework—0
Evaluating Point Cloud from Moving Camera Videos: A No-Reference MetricCode0
Learning Human Cognitive Appraisal Through Reinforcement Memory Unit—0
Telepresence Video Quality Assessment—0
Multiview Contrastive Learning for Completely Blind Video Quality Assessment of User Generated ContentCode0
Subjective and Objective Quality Assessment of High-Motion Sports Videos at Low-BitratesCode0
Exploring the Effectiveness of Video Perceptual Representation in Blind Video Quality AssessmentCode0
DisCoVQA: Temporal Distortion-Content Transformers for Video Quality AssessmentCode0
Perceptual Quality Assessment of Virtual Reality Videos in the WildCode0
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions—0
A Framework to Map VMAF with the Probability of Just Noticeable Difference between Video Encoding Recipes—0
Deep Quality Assessment of Compressed Videos: A Subjective and Objective Study—0
Perceptual Quality Assessment of UGC Gaming Videos—0
Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessment—0
Subjective and Objective Analysis of Streamed Gaming Videos—0
RankDVQA: Deep VQA based on Ranking-inspired Hybrid Training—0
A Neural Network based Framework for Effective Laparoscopic Video Quality AssessmentCode0
No-Reference Video Quality Assessment Based on Benford’s Law and Perceptual FeaturesCode0
Locally Adaptive Structure and Texture Similarity for Image Quality Assessment—0
PRNet: A Progressive Regression Network for No-Reference User-Generated-Content Video Quality Assessment—0
High Frame Rate Video Quality Assessment using VMAF and Entropic Differences—0
A survey on IQA—0
StarVQA: Space-Time Attention for Video Quality AssessmentCode0
FOVQA: Blind Foveated Video Quality Assessment—0
Rich Features for Perceptual Quality Assessment of UGC Videos—0
Assessment of Subjective and Objective Quality of Live Streaming Sports Videos—0
Improving precision of objective image/video quality metrics—0
Joint Optimization for SSIM-Based CTU-Level Bit Allocation and Rate Distortion OptimizationCode0
VMAF And Variants: Towards A Unified VQA—0
Enhancing VMAF through New Feature Integration and Model Combination—0
Latent Factor Modeling of Users Subjective Perception for Stereoscopic 3D Video Recommendation—0
Study on the Assessment of the Quality of Experience of Streaming VideoCode0
Critical analysis on the reproducibility of visual quality assessment using deep featuresCode0
No-Reference Video Quality Assessment Using Space-Time ChipsCode0
Capturing Video Frame Rate Variations via Entropic Differencing—0
Comment on "No-Reference Video Quality Assessment Based on the Temporal Pooling of Deep Features"—0
A Comparative Evaluation of Temporal Pooling Methods for Blind Video Quality Assessment—0
From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture QualityCode0
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild—0
C3DVQA: Full-Reference Video Quality Assessment with 3D Convolutional Neural Network—0
Test-Time Training with Self-Supervision for Generalization under Distribution ShiftsCode0
Quality Assessment of In-the-Wild VideosCode0
Barriers towards no-reference metrics application to compressed video quality analysis: on the example of no-reference metric NIQE—0
Two-Level Approach for No-Reference Consumer Video Quality AssessmentCode0
Viewport Proposal CNN for 360deg Video Quality AssessmentCode0
PEA265: Perceptual Assessment of Video Compression Artifacts—0
Power of Tempospatially Unified Spectral Density for Perceptual Video Quality AssessmentCode0
UNIQUE: Unsupervised Image Quality EstimationCode0
Prediction of the Influence of Navigation Scan-path on Perceived Quality of Free-Viewpoint Videos—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 (v063)SRCC0.94—Unverified
2VMAF Y (v061)SRCC0.94—Unverified
3VMAF Y (v062)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