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Video Quality Assessment
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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.
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EyeSim-VQA: A Free-Energy-Guided Eye Simulation Framework for Video Quality Assessment
TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs
NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results
CP-LLM: Context and Pixel Aware Large Language Model for Video Quality Assessment
Semantically-Aware Game Image Quality Assessment
DiffVQA: Video Quality Assessment Using Diffusion Feature Extractor
Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results
DVLTA-VQA: Decoupled Vision-Language Modeling with Text-Guided Adaptation for Blind Video Quality Assessment
FVQ: A Large-Scale Dataset and A LMM-based Method for Face Video Quality Assessment
AMD-Hummingbird: Towards an Efficient Text-to-Video Model
KVQ: Boosting Video Quality Assessment via Saliency-guided Local Perception
Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language Model
Adaptive Score Alignment Learning for Continual Perceptual Quality Assessment of 360-Degree Videos in Virtual Reality
InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model
Content-Rich AIGC Video Quality Assessment via Intricate Text Alignment and Motion-Aware Consistency
A Multi-annotated and Multi-modal Dataset for Wide-angle Video Quality Assessment
Cross-Modal Transferable Image-to-Video Attack on Video Quality Metrics
Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling
Multilevel Semantic-Aware Model for AI-Generated Video Quality Assessment
VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation
ESVQA: Perceptual Quality Assessment of Egocentric Spatial Videos
FineVQ: Fine-Grained User Generated Content Video Quality Assessment
TINQ: Temporal Inconsistency Guided Blind Video Quality Assessment
An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM
OnlineVPO: Align Video Diffusion Model with Online Video-Centric Preference Optimization
Video Quality Assessment: A Comprehensive Survey
Subjective and Objective Quality Assessment Methods of Stereoscopic Videos with Visibility Affecting Distortions
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMM
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric
VQA$^2$: Visual Question Answering for Video Quality Assessment
Deep Priors for Video Quality Prediction
Latent Image and Video Resolution Prediction using Convolutional Neural Networks
Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities
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