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Subjective and Objective Audio-Visual Quality Assessment for User Generated Content
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-031-19836-6_19openalex-snapshot
Telepresence Video Quality Assessment
inferredcites →https://doi.org/10.1007/s11042-018-5656-7openalex-snapshot
Combining audio and video metrics to assess audio-visual quality
inferredcites →https://doi.org/10.1016/b978-0-08-099388-1.00010-8openalex-snapshot
Introduction to Audio Analysis: A MATLAB Approach
inferredcites →https://doi.org/10.1109/78.650093openalex-snapshot
Bidirectional recurrent neural networks
inferredcites →https://doi.org/10.1109/cvpr.2012.6247789openalex-snapshot
Unsupervised feature learning framework for no-reference image quality assessment
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00373openalex-snapshot
Perceptual Quality Assessment of Smartphone Photography
inferredcites →https://doi.org/10.1109/icc.2016.7511101openalex-snapshot
Towards reduced reference parametric models for estimating audiovisual quality in multimedia services
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/icip42928.2021.9506420openalex-snapshot
Attention Based Network For No-Reference UGC Video Quality Assessment
inferredcites →https://doi.org/10.1109/icip49359.2023.10222476openalex-snapshot
Audio-Visual Quality Assessment for User Generated Content: Database and Method
inferredcites →https://doi.org/10.1109/icmew53276.2021.9455999openalex-snapshot
Deep Learning Based Full-Reference and No-Reference Quality Assessment Models for Compressed UGC Videos
inferredcites →https://doi.org/10.1109/jstsp.2012.2215007openalex-snapshot
Analysis of Public Image and Video Databases for Quality Assessment
inferredcites →https://doi.org/10.1109/jstsp.2019.2955024openalex-snapshot
MC360IQA: A Multi-channel CNN for Blind 360-Degree Image Quality Assessment
inferredcites →https://doi.org/10.1109/jstsp.2023.3270621openalex-snapshot
Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion and Iterative Mixed Database Training
inferredcites →https://doi.org/10.1109/lsp.2012.2227726openalex-snapshot
Making a “Completely Blind” Image Quality Analyzer
inferredcites →https://doi.org/10.1109/mmsp.2019.8901772openalex-snapshot
YouTube UGC Dataset for Video Compression Research
inferredcites →https://doi.org/10.1109/ojsp.2021.3090333openalex-snapshot
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
inferredcites →https://doi.org/10.1109/qomex.2016.7498974openalex-snapshot
Perception and automated assessment of audio quality in user generated content: An improved model
inferredcites →https://doi.org/10.1109/qomex.2017.7965673openalex-snapshot
The Konstanz natural video database (KoNViD-1k)
inferredcites →https://doi.org/10.1109/tbc.2022.3221689openalex-snapshot
Deep Neural Network for Blind Visual Quality Assessment of 4K Content
inferredcites →https://doi.org/10.1109/tcsvt.2017.2707479openalex-snapshot
In-Capture Mobile Video Distortions: A Study of Subjective Behavior and Objective Algorithms
inferredcites →https://doi.org/10.1109/tcsvt.2022.3164467openalex-snapshot
Blindly Assess Quality of In-the-Wild Videos via Quality-Aware Pre-Training and Motion Perception
inferredcites →https://doi.org/10.1109/tip.2010.2053549openalex-snapshot
No-Reference Blur Assessment of Digital Pictures Based on Multifeature Classifiers
inferredcites →https://doi.org/10.1109/tip.2011.2131660openalex-snapshot
A No-Reference Image Blur Metric Based on the Cumulative Probability of Blur Detection (CPBD)
inferredcites →https://doi.org/10.1109/tip.2012.2214050openalex-snapshot
No-Reference Image Quality Assessment in the Spatial Domain
inferredcites →https://doi.org/10.1109/tip.2014.2299154openalex-snapshot
Blind Prediction of Natural Video Quality
inferredcites →https://doi.org/10.1109/tip.2015.2500021openalex-snapshot
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
inferredcites →https://doi.org/10.1109/tip.2017.2685941openalex-snapshot
No-Reference Quality Assessment of Tone-Mapped HDR Pictures
inferredcites →https://doi.org/10.1109/tip.2018.2869673openalex-snapshot
Large-Scale Study of Perceptual Video Quality
inferredcites →https://doi.org/10.1109/tip.2019.2922850openalex-snapshot
Predicting the Quality of Images Compressed After Distortion in Two Steps
inferredcites →https://doi.org/10.1109/tip.2019.2923051openalex-snapshot
Two-Level Approach for No-Reference Consumer Video Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2020.2966082openalex-snapshot
A Multimodal Saliency Model for Videos With High Audio-Visual Correspondence
inferredcites →https://doi.org/10.1109/tip.2020.2967829openalex-snapshot
KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment
inferredcites →https://doi.org/10.1109/tip.2020.2988148openalex-snapshot
Study of Subjective and Objective Quality Assessment of Audio-Visual Signals
inferredcites →https://doi.org/10.1109/tip.2021.3072221openalex-snapshot
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
inferredcites →https://doi.org/10.1109/tip.2023.3251695openalex-snapshot
Attention-Guided Neural Networks for Full-Reference and No-Reference Audio-Visual Quality Assessment
inferredcites →https://doi.org/10.1109/tmc.2020.3004534openalex-snapshot
Dynamic Backlight Scaling Considering Ambient Luminance for Mobile Videos on LCD Displays
inferredcites →https://doi.org/10.1117/12.477378openalex-snapshot
Measuring colorfulness in natural images
inferredcites →https://doi.org/10.1145/2502081.2502106openalex-snapshot
Non-reference audio quality assessment for online live music recordings
inferredcites →https://doi.org/10.1145/3503161.3547872openalex-snapshot
Image Quality Assessment: From Mean Opinion Score to Opinion Score Distribution
inferredcites →https://doi.org/10.1145/3503161.3548329openalex-snapshot
A Deep Learning based No-reference Quality Assessment Model for UGC Videos
inferredcites →https://doi.org/10.21437/interspeech.2020-1303openalex-snapshot
Environment Sound Classification Using Multiple Feature Channels and Attention Based Deep Convolutional Neural Network
inferredcites →https://doi.org/10.23919/eusipco.2019.8902975openalex-snapshot
NAViDAd: A No-Reference Audio-Visual Quality Metric Based on a Deep Autoencoder
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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DELIA-Net: A Detail-Enhanced and Local Illumination Adjustment Network for nighttime road image enhancement
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A Deep Cross-modal Prompt Learning Network for Artificial Intelligence Generated Image Quality Assessment
inferred← citeshttps://doi.org/10.1016/j.displa.2025.103232openalex-snapshot
Dual-stage attention based symmetric framework for stereo video quality assessment
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TDtoon: Two-stage diffusion for controllable cartoon video generation via sketch enhancement
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PU-MG: Mutual guidance framework for Point Cloud Upsampling
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MFHOD: Multi-modal image fusion method based on the higher-order degradation model
inferred← citeshttps://doi.org/10.1016/j.image.2026.117596openalex-snapshot
Video quality assessment motivated by reverse hierarchy with feedforward and feedback perception representations
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104519openalex-snapshot
Listen2Track: Plug-and-play audio-visual matching for generic multi-object tracking
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Alternative audio-graphic method for presenting structural information in mathematical graphs designed for low-vision users
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A Multi-annotated and Multi-modal Dataset for Wide-angle Video Quality Assessment
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SFQA: A Comprehensive Perceptual Quality Assessment Dataset for Singing Face Generation
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Perceptual Audio-Visual Quality Assessment for Compressed Professionally-Generated Content: A New Dataset and An Effective Method
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Calculating Color Differences of Images via Siamese Neural Network
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Enhancing No-Reference Audio-Visual Quality Assessment via Joint Cross-Attention Fusion
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Large-Scale Medical Records Analysis by AI-Driven Method in Healthcare Consumer Electronics
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UNQA: Unified No-Reference Quality Assessment for Audio, Image, Video, and Audio-Visual Content
inferred← citeshttps://doi.org/10.1109/tcsvt.2026.3674552openalex-snapshot
Multi-Branch Aesthetic and Technical Perspectives With Cross Tri-Fusion Attention for No-Reference Audio-Visual Quality Assessment
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How is Visual Attention Influenced by Text Guidance? Database and Model
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Consistency-Queried Transformer for Audio-Visual Segmentation
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Blind Image Quality Assessment via Transformer Predicted Error Map and Perceptual Quality Token
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CNN-Based 360$^{\circ }$ Scene Recognition for Automatic Generation of Omnidirectional Scent Effects
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2BiVQA: Double Bi-LSTM-based Video Quality Assessment of UGC Videos
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FLAME-VQA: A Fuzzy Logic-Based Model for High Frame Rate Video Quality Assessment
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A quality assessment algorithm for no-reference images based on transfer learning
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