Video Quality Assessment
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Benchmarks
MSU SR-QA Dataset
KoNViD-1k
MSU NR VQA Database
LIVE-VQC
MSU FR VQA Database
YouTube-UGC
LIVE-FB LSVQ
LIVE-ETRI
LIVE Livestream
LIVE-YT-HFR
Most implemented
Towards Deep Learning Models Resistant to Adversarial Attacks
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Visualizing and Understanding Convolutional Networks
NIMA: Neural Image Assessment
The 2018 PIRM Challenge on Perceptual Image Super-resolution
Papers
High-Fidelity Video Quality Assessment with VQA-Specific Saliency
No-reference video quality assessment (NR VQA) has recently seen promising progress with deep learning. However, video data is inherently large, and processing them with deep models incurs high computational cost. This c…
Video Quality AssessmentCamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation
Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-defined camera trajectories. However, existing video quality assessment (V…
Video Quality AssessmentVideo GenerationContrastive Order Learning: A General Framework for Ordinal Regression
We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. While contrastive learning effectively lev…
Image Quality AssessmentVideo Quality AssessmentContrastive LearningAge EstimationLearning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions
Video quality assessment (VQA) plays a critical role in optimizing video delivery systems. While numerous objective metrics have been proposed to approximate human perception, the perceived quality strongly depends on vi…
Video Quality AssessmentCompressedVQA-AEV: Full-Reference and No-Reference Quality Assessment Models for Asymmetric Encoded Videos
This report presents our solutions to the QoMEX 2026 Grand Challenge on Video Quality Assessment for Asymmetric Encoded Videos, comprising a full-reference (FR) model, CompressedVQA-AEV-FR, and a no-reference (NR) model,…
Video Quality AssessmentCommunity-Aware Assessment of Social Textual Engagement and Resonance: A Human-Centric Perspective on User-Generated Content Evaluation
Traditional Video Quality Assessment (VQA) focuses narrowly on aesthetic fidelity, overlooking the complex social dynamics that define quality in User-Generated Content (UGC). In this work, we propose a paradigm shift fr…
Video Quality AssessmentReinforcement Learning