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2BiVQA: Double Bi-LSTM-based Video Quality Assessment of UGC Videos
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Outgoing claims: the papers this work cites, builds on, or argues with.
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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Perceptual image quality assessment: a survey
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C-DIIVINE: No-reference image quality assessment based on local magnitude and phase statistics of natural scenes
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DeepSim: Deep similarity for image quality assessment
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Deep feature importance awareness based no-reference image quality prediction
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Framewise phoneme classification with bidirectional LSTM and other neural network architectures
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Statistics of natural images: Scaling in the woods
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Bidirectional recurrent neural networks
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A Survey of DNN Methods for Blind Image Quality Assessment
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KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild
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ImageNet: A large-scale hierarchical image database
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Convolutional Neural Networks for No-Reference Image Quality Assessment
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Deep Residual Learning for Image Recognition
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Densely Connected Convolutional Networks
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
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From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality
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Proceedings 2001 International Conference On Image Processing
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XGC-VQA: A Unified Video Quality Assessment Model for User, Professionally, and Occupationally-Generated Content
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Considering Temporal Variations of Spatial Visual Distortions in Video Quality Assessment
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Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion and Iterative Mixed Database Training
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A Two-Step Framework for Constructing Blind Image Quality Indices
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A DCT Statistics-Based Blind Image Quality Index
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Making a “Completely Blind” Image Quality Analyzer
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No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model
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Deep Convolutional Neural Models for Picture-Quality Prediction: Challenges and Solutions to Data-Driven Image Quality Assessment
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RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
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Hybrid No-Reference Quality Metric for Singly and Multiply Distorted Images
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Blind Image Quality Estimation via Distortion Aggravation
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An End-to-End No-Reference Video Quality Assessment Method With Hierarchical Spatiotemporal Feature Representation
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Study of Subjective and Objective Quality Assessment of Video
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Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
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Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain
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No-Reference Image Quality Assessment in the Spatial Domain
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Video Quality Pooling Adaptive to Perceptual Distortion Severity
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Blind Prediction of Natural Video Quality
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Blind Image Quality Assessment Using Joint Statistics of Gradient Magnitude and Laplacian Features
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A Feature-Enriched Completely Blind Image Quality Evaluator
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Image Quality Assessment Using Human Visual DOG Model Fused With Random Forest
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Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
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A Completely Blind Video Integrity Oracle
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Spatiotemporal Statistics for Video Quality Assessment
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Blind Image Quality Assessment Based on High Order Statistics Aggregation
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No-Reference Quality Assessment of Tone-Mapped HDR Pictures
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Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images
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Large-Scale Study of Perceptual Video Quality
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Two-Level Approach for No-Reference Consumer Video Quality Assessment
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KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment
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Study of Subjective and Objective Quality Assessment of Audio-Visual Signals
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UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
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Completely Blind Quality Assessment of User Generated Video Content
inferredcites →https://doi.org/10.1109/tip.2023.3290528openalex-snapshot
Subjective and Objective Audio-Visual Quality Assessment for User Generated Content
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Blind Quality Assessment Based on Pseudo-Reference Image
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No-reference image quality assessment based on log-derivative statistics of natural scenes
inferredcites →https://doi.org/10.1117/12.645089openalex-snapshot
Measurement of ringing artifacts in JPEG images
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The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions
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Aesthetics-Guided Summarization from Multiple User Generated Videos
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End-to-End Blind Quality Assessment of Compressed Videos Using Deep Neural Networks
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Quality Assessment of In-the-Wild Videos
inferredcites →https://doi.org/10.1145/3414837openalex-snapshot
Blind Image Quality Assessment by Natural Scene Statistics and Perceptual Characteristics
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Mimicking Individual Media Quality Perception with Neural Network based Artificial Observers
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Screen Content Quality Assessment: Overview, Benchmark, and Beyond
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Perceptual Quality Assessment of Internet Videos
inferredcites →https://doi.org/10.1145/3503161.3548064openalex-snapshot
Multiview Contrastive Learning for Completely Blind Video Quality Assessment of User Generated Content
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A Deep Learning based No-reference Quality Assessment Model for UGC Videos
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Perceptual quality prediction on authentically distorted images using a bag of features approach
inferredcites →https://doi.org/10.2352/j.imagingsci.technol.2016.60.6.060410openalex-snapshot
Image Quality Assessment by Comparing CNN Features between Images
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Fast and reliable structure-oriented video noise estimation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-95-5740-0_25openalex-snapshot
MMVQA: Dual-Path Multimodal Fusion for AI-Generated Video Quality Assessment
inferred← citeshttps://doi.org/10.1007/s00530-026-02416-5openalex-snapshot
An efficient video quality assessment model incorporating VideoMamba and dual-dimensional attention
inferred← citeshttps://doi.org/10.1007/s11432-024-4133-3openalex-snapshot
Perceptual video quality assessment: a survey
inferred← citeshttps://doi.org/10.1007/s11760-025-04151-2openalex-snapshot
DC-HCVQA: a dark channel enhanced human cognitive system based video quality assessment
inferred← citeshttps://doi.org/10.1016/j.displa.2024.102792openalex-snapshot
ADS-VQA: Adaptive sampling model for video quality assessment
inferred← citeshttps://doi.org/10.1016/j.displa.2025.103259openalex-snapshot
Spatio-temporal attention feature fusion: A video quality assessment method for User-Generated Content
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113491openalex-snapshot
No-reference video quality assessment based on spatio-temporal perception information
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.130852openalex-snapshot
Memory-VQA: Video quality assessment of UGC based on human memory system
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11582042openalex-snapshot
No-reference video quality assessment with guidance of keyframe extraction
inferred← citeshttps://doi.org/10.1109/iisa62523.2024.10786685openalex-snapshot
Reliability of CNN-Based No-Reference Video Quality Metrics
inferred← citeshttps://doi.org/10.1109/smc58881.2025.11343375openalex-snapshot
SCCOME: Scene Change Capture and Optical Motion Estimation for Video Quality Assessment
inferred← citeshttps://doi.org/10.1109/tbc.2023.3312932openalex-snapshot
Integrates Spatiotemporal Visual Stimuli for Video Quality Assessment
inferred← citeshttps://doi.org/10.1109/tcsvt.2024.3469180openalex-snapshot
A No-Reference Quality Assessment Model for Screen Content Videos via Hierarchical Spatiotemporal Perception
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3585993openalex-snapshot
Blind Quality Assessment of Wide-Angle Videos Based on Deformation Representation Learning and Multi-Dimensional Feature Fusion
inferred← citeshttps://doi.org/10.1109/tcsvt.2026.3679733openalex-snapshot
Ultra-High-Definition Video Quality Assessment Based on Adaptively Spatial Fusion and Temporal Selection
inferred← citeshttps://doi.org/10.1145/3664647.3680598openalex-snapshot
Semantic-Aware and Quality-Aware Interaction Network for Blind Video Quality Assessment
inferred← citeshttps://doi.org/10.1145/3820054openalex-snapshot
GSAlign: Optical Alignment for Photorealistic Dynamic 3D Reconstruction from UGC in Web3
inferred← citeshttps://doi.org/10.1145/3822174openalex-snapshot
IBCL-VQA: Video Quality Assessment with In-Batch Contrastive Learning and Two-Phase Feature Fusion
inferred← citeshttps://doi.org/10.3390/fire7060200openalex-snapshot
Predict Future Transient Fire Heat Release Rates Based on Fire Imagery and Deep Learning
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