{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/video-quality-assessment/papers/2","list_of":"/task/video-quality-assessment","task":"Video Quality Assessment","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":3,"rows_per_page":100,"rows":[101,200],"of":216,"counts":{"archive_papers_tagged":216,"with_a_code_link":116,"where_syntology_ran_a_sample":20,"not_listed_spam_title":0,"listed":216,"listed_where_code_ran":20,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":17,"every_run_a_failure_of_syntologys_instrument":3,"listed_with_a_run_with_no_instrument_failure":17,"listed_every_run_a_failure_of_syntologys_instrument":3,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/video-quality-assessment","prev":"/task/video-quality-assessment","next":"/task/video-quality-assessment/papers/3","papers":[{"url":"/paper/deep-learning-based-full-reference-and-no","slug":"deep-learning-based-full-reference-and-no","title":"Deep Learning based Full-reference and No-reference Quality Assessment Models for Compressed UGC Videos","date":"2021-06-02","arxiv_id":"2106.01111","repositories_listed":1,"syntology":null},{"url":"/paper/joint-optimization-for-ssim-based-ctu-level","slug":"joint-optimization-for-ssim-based-ctu-level","title":"Joint Optimization for SSIM-Based CTU-Level Bit Allocation and Rate Distortion Optimization","date":"2021-04-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/rapique-rapid-and-accurate-video-quality","slug":"rapique-rapid-and-accurate-video-quality","title":"RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content","date":"2021-01-26","arxiv_id":"2101.10955","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-curriculum-domain-adaptation-for","slug":"unsupervised-curriculum-domain-adaptation-for","title":"Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality Assessment","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/learning-generalized-spatial-temporal-deep","slug":"learning-generalized-spatial-temporal-deep","title":"Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment","date":"2020-12-27","arxiv_id":"2012.13936","repositories_listed":1,"syntology":null},{"url":"/paper/patch-vq-patching-up-the-video-quality","slug":"patch-vq-patching-up-the-video-quality","title":"Patch-VQ: 'Patching Up' the Video Quality Problem","date":"2020-11-27","arxiv_id":"2011.13544","repositories_listed":1,"syntology":null},{"url":"/paper/unified-quality-assessment-of-in-the-wild","slug":"unified-quality-assessment-of-in-the-wild","title":"Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training","date":"2020-11-09","arxiv_id":"2011.04263","repositories_listed":1,"syntology":null},{"url":"/paper/st-greed-space-time-generalized-entropic","slug":"st-greed-space-time-generalized-entropic","title":"ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction","date":"2020-10-26","arxiv_id":"2010.13715","repositories_listed":1,"syntology":null},{"url":"/paper/critical-analysis-on-the-reproducibility-of","slug":"critical-analysis-on-the-reproducibility-of","title":"Critical analysis on the reproducibility of visual quality assessment using deep features","date":"2020-09-10","arxiv_id":"2009.05369","repositories_listed":1,"syntology":null},{"url":"/paper/no-reference-video-quality-assessment-using-1","slug":"no-reference-video-quality-assessment-using-1","title":"No-Reference Video Quality Assessment Using Space-Time Chips","date":"2020-08-23","arxiv_id":"2008.00031","repositories_listed":1,"syntology":null},{"url":"/paper/active-sampling-for-pairwise-comparisons-via","slug":"active-sampling-for-pairwise-comparisons-via","title":"Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization","date":"2020-04-12","arxiv_id":"2004.05691","repositories_listed":1,"syntology":null},{"url":"/paper/two-level-approach-for-no-reference-consumer","slug":"two-level-approach-for-no-reference-consumer","title":"Two-Level Approach for No-Reference Consumer Video Quality Assessment","date":"2019-06-20","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/viewport-proposal-cnn-for-360deg-video","slug":"viewport-proposal-cnn-for-360deg-video","title":"Viewport Proposal CNN for 360deg Video Quality Assessment","date":"2019-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/pieapp-perceptual-image-error-assessment","slug":"pieapp-perceptual-image-error-assessment","title":"PieAPP: Perceptual Image-Error Assessment through Pairwise Preference","date":"2018-06-06","arxiv_id":"1806.02067","repositories_listed":1,"syntology":null},{"url":"/paper/spatiotemporal-feature-integration-and-model","slug":"spatiotemporal-feature-integration-and-model","title":"SpatioTemporal Feature Integration and Model Fusion for Full Reference Video Quality Assessment","date":"2018-04-13","arxiv_id":"1804.04813","repositories_listed":1,"syntology":null},{"url":"/paper/blind-prediction-of-natural-video-quality","slug":"blind-prediction-of-natural-video-quality","title":"Blind Prediction of Natural Video Quality","date":"2014-01-09","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":null,"slug":"bridging-video-quality-scoring-and","title":"Bridging Video Quality Scoring and Justification via Large Multimodal Models","date":"2025-06-26","arxiv_id":"2506.21011","repositories_listed":0,"syntology":null},{"url":null,"slug":"eyesim-vqa-a-free-energy-guided-eye","title":"EyeSim-VQA: A Free-Energy-Guided Eye Simulation Framework for Video Quality Assessment","date":"2025-06-13","arxiv_id":"2506.11549","repositories_listed":0,"syntology":null},{"url":null,"slug":"tdve-assessor-benchmarking-and-evaluating-the","title":"TDVE-Assessor: Benchmarking and Evaluating the Quality of Text-Driven Video Editing with LMMs","date":"2025-05-26","arxiv_id":"2505.19535","repositories_listed":0,"syntology":null},{"url":null,"slug":"cp-llm-context-and-pixel-aware-large-language","title":"CP-LLM: Context and Pixel Aware Large Language Model for Video Quality Assessment","date":"2025-05-21","arxiv_id":"2505.16025","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantically-aware-game-image-quality","title":"Semantically-Aware Game Image Quality Assessment","date":"2025-05-16","arxiv_id":"2505.11724","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffvqa-video-quality-assessment-using","title":"DiffVQA: Video Quality Assessment Using Diffusion Feature Extractor","date":"2025-05-06","arxiv_id":"2505.03261","repositories_listed":0,"syntology":null},{"url":null,"slug":"ntire-2025-challenge-on-short-form-ugc-video-1","title":"NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study","date":"2025-04-21","arxiv_id":"2504.15003","repositories_listed":0,"syntology":null},{"url":null,"slug":"dvlta-vqa-decoupled-vision-language-modeling","title":"DVLTA-VQA: Decoupled Vision-Language Modeling with Text-Guided Adaptation for Blind Video Quality Assessment","date":"2025-04-16","arxiv_id":"2504.11733","repositories_listed":0,"syntology":null},{"url":null,"slug":"internvqa-advancing-compressed-video-quality","title":"InternVQA: Advancing Compressed Video Quality Assessment with Distilling Large Foundation Model","date":"2025-02-26","arxiv_id":"2502.19026","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-annotated-and-multi-modal-dataset-for","title":"A Multi-annotated and Multi-modal Dataset for Wide-angle Video Quality Assessment","date":"2025-01-21","arxiv_id":"2501.12082","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-quality-assessment-for-online","title":"Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling","date":"2025-01-13","arxiv_id":"2501.07087","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilevel-semantic-aware-model-for-ai","title":"Multilevel Semantic-Aware Model for AI-Generated Video Quality Assessment","date":"2025-01-06","arxiv_id":"2501.02706","repositories_listed":0,"syntology":null},{"url":null,"slug":"esvqa-perceptual-quality-assessment-of","title":"ESVQA: Perceptual Quality Assessment of Egocentric Spatial Videos","date":"2024-12-29","arxiv_id":"2412.20423","repositories_listed":0,"syntology":null},{"url":null,"slug":"finevq-fine-grained-user-generated-content","title":"FineVQ: Fine-Grained User Generated Content Video Quality Assessment","date":"2024-12-26","arxiv_id":"2412.19238","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-ensemble-approach-to-short-form-video","title":"An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM","date":"2024-12-24","arxiv_id":"2412.18060","repositories_listed":0,"syntology":null},{"url":null,"slug":"onlinevpo-align-video-diffusion-model-with","title":"OnlineVPO: Align Video Diffusion Model with Online Video-Centric Preference Optimization","date":"2024-12-19","arxiv_id":"2412.15159","repositories_listed":0,"syntology":null},{"url":null,"slug":"subjective-and-objective-quality-assessment-6","title":"Subjective and Objective Quality Assessment Methods of Stereoscopic Videos with Visibility Affecting Distortions","date":"2024-11-29","arxiv_id":"2411.19522","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-activity-agv-quality-assessment-a","title":"Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric","date":"2024-11-25","arxiv_id":"2411.16619","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-priors-for-video-quality-prediction","title":"Deep Priors for Video Quality Prediction","date":"2024-10-29","arxiv_id":"2410.22566","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-image-and-video-resolution-prediction","title":"Latent Image and Video Resolution Prediction using Convolutional Neural Networks","date":"2024-10-17","arxiv_id":"2410.13227","repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-prediction-of-ai-generated-images-and","title":"Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities","date":"2024-10-11","arxiv_id":"2410.08534","repositories_listed":0,"syntology":null},{"url":null,"slug":"secure-video-quality-assessment-resisting","title":"Secure Video Quality Assessment Resisting Adversarial Attacks","date":"2024-10-09","arxiv_id":"2410.06866","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-video-quality-assessment-for-aigc","title":"Advancing Video Quality Assessment for AIGC","date":"2024-09-23","arxiv_id":"2409.14888","repositories_listed":0,"syntology":null},{"url":null,"slug":"lmm-vqa-advancing-video-quality-assessment","title":"LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models","date":"2024-08-26","arxiv_id":"2408.14008","repositories_listed":0,"syntology":null},{"url":null,"slug":"bvi-ugc-a-video-quality-database-for-user","title":"BVI-UGC: A Video Quality Database for User-Generated Content Transcoding","date":"2024-08-13","arxiv_id":"2408.07171","repositories_listed":0,"syntology":null},{"url":null,"slug":"subjective-and-objective-quality-assessment-5","title":"Subjective and Objective Quality Assessment of Rendered Human Avatar Videos in Virtual Reality","date":"2024-08-13","arxiv_id":"2408.07041","repositories_listed":0,"syntology":null},{"url":null,"slug":"benchmarking-aigc-video-quality-assessment-a","title":"Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model","date":"2024-07-31","arxiv_id":"2407.21408","repositories_listed":0,"syntology":null},{"url":null,"slug":"highly-efficient-no-reference-4k-video","title":"Highly Efficient No-reference 4K Video Quality Assessment with Full-Pixel Covering Sampling and Training Strategy","date":"2024-07-30","arxiv_id":"2407.20766","repositories_listed":0,"syntology":null},{"url":null,"slug":"priorformer-a-ugc-vqa-method-with-content-and","title":"Priorformer: A UGC-VQA Method with content and distortion priors","date":"2024-06-24","arxiv_id":"2406.16297","repositories_listed":0,"syntology":null},{"url":null,"slug":"mantisscore-building-automatic-metrics-to","title":"VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation","date":"2024-06-21","arxiv_id":"2406.15252","repositories_listed":0,"syntology":null},{"url":null,"slug":"mvad-a-multiple-visual-artifact-detector-for","title":"MVAD: A Multiple Visual Artifact Detector for Video Streaming","date":"2024-05-31","arxiv_id":"2406.00212","repositories_listed":0,"syntology":null},{"url":null,"slug":"ptm-vqa-efficient-video-quality-assessment","title":"PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild","date":"2024-05-28","arxiv_id":"2405.17765","repositories_listed":0,"syntology":null},{"url":null,"slug":"rmt-bvqa-recurrent-memory-transformer-based","title":"RMT-BVQA: Recurrent Memory Transformer-based Blind Video Quality Assessment for Enhanced Video Content","date":"2024-05-14","arxiv_id":"2405.08621","repositories_listed":0,"syntology":null},{"url":null,"slug":"ntire-2024-quality-assessment-of-ai-generated","title":"NTIRE 2024 Quality Assessment of AI-Generated Content Challenge","date":"2024-04-25","arxiv_id":"2404.16687","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcqa-a-strong-baseline-for-aigc-quality","title":"PCQA: A Strong Baseline for AIGC Quality Assessment Based on Prompt Condition","date":"2024-04-20","arxiv_id":"2404.13299","repositories_listed":0,"syntology":null},{"url":null,"slug":"study-of-the-effect-of-sharpness-on-blind","title":"Study of the effect of Sharpness on Blind Video Quality Assessment","date":"2024-04-06","arxiv_id":"2404.05764","repositories_listed":0,"syntology":null},{"url":null,"slug":"perceptual-video-quality-assessment-a-survey","title":"Perceptual Video Quality Assessment: A Survey","date":"2024-02-05","arxiv_id":"2402.03413","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-quality-assessment-based-on-swin","title":"Video Quality Assessment Based on Swin TransformerV2 and Coarse to Fine Strategy","date":"2024-01-16","arxiv_id":"2401.08522","repositories_listed":0,"syntology":null},{"url":null,"slug":"q-boost-on-visual-quality-assessment-ability","title":"Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models","date":"2023-12-23","arxiv_id":"2312.15300","repositories_listed":0,"syntology":null},{"url":null,"slug":"full-reference-video-quality-assessment-for-1","title":"Full-reference Video Quality Assessment for User Generated Content Transcoding","date":"2023-12-19","arxiv_id":"2312.12317","repositories_listed":0,"syntology":null},{"url":null,"slug":"rankdvqa-mini-knowledge-distillation-driven","title":"RankDVQA-mini: Knowledge Distillation-Driven Deep Video Quality Assessment","date":"2023-12-14","arxiv_id":"2312.08864","repositories_listed":0,"syntology":null},{"url":null,"slug":"clif-vqa-enhancing-video-quality-assessment","title":"CLiF-VQA: Enhancing Video Quality Assessment by Incorporating High-Level Semantic Information related to Human Feelings","date":"2023-11-13","arxiv_id":"2311.07090","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometry-aware-video-quality-assessment-for","title":"Geometry-Aware Video Quality Assessment for Dynamic Digital Human","date":"2023-10-24","arxiv_id":"2310.15984","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-quality-assessment-and-coding","title":"Video Quality Assessment and Coding Complexity of the Versatile Video Coding Standard","date":"2023-10-19","arxiv_id":"2310.13093","repositories_listed":0,"syntology":null},{"url":null,"slug":"ada-dqa-adaptive-diverse-quality-aware","title":"Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment","date":"2023-08-01","arxiv_id":"2308.00729","repositories_listed":0,"syntology":null},{"url":null,"slug":"capturing-co-existing-distortions-in-user","title":"Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessment","date":"2023-07-31","arxiv_id":"2307.16813","repositories_listed":0,"syntology":null},{"url":null,"slug":"ntire-2023-quality-assessment-of-video","title":"NTIRE 2023 Quality Assessment of Video Enhancement Challenge","date":"2023-07-19","arxiv_id":"2307.09729","repositories_listed":0,"syntology":null},{"url":null,"slug":"blind-video-quality-assessment-at-the-edge","title":"Blind Video Quality Assessment at the Edge","date":"2023-06-17","arxiv_id":"2306.10386","repositories_listed":0,"syntology":null},{"url":null,"slug":"study-of-subjective-and-objective-quality","title":"Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos","date":"2023-05-26","arxiv_id":"2305.17260","repositories_listed":0,"syntology":null},{"url":null,"slug":"sb-vqa-a-stack-based-video-quality-assessment","title":"SB-VQA: A Stack-Based Video Quality Assessment Framework for Video Enhancement","date":"2023-05-15","arxiv_id":"2305.08408","repositories_listed":0,"syntology":null},{"url":null,"slug":"hdr-vdp-3-a-multi-metric-for-predicting-image","title":"HDR-VDP-3: A multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content","date":"2023-04-26","arxiv_id":"2304.13625","repositories_listed":0,"syntology":null},{"url":null,"slug":"hdr-chipqa-no-reference-quality-assessment-on","title":"HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videos","date":"2023-04-25","arxiv_id":"2304.13156","repositories_listed":0,"syntology":null},{"url":null,"slug":"making-video-quality-assessment-models-robust","title":"Making Video Quality Assessment Models Robust to Bit Depth","date":"2023-04-25","arxiv_id":"2304.13092","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-transform-to-compute-them-all-efficient","title":"One Transform To Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment","date":"2023-04-06","arxiv_id":"2304.03412","repositories_listed":0,"syntology":null},{"url":null,"slug":"mret-multi-resolution-transformer-for-video","title":"MRET: Multi-resolution Transformer for Video Quality Assessment","date":"2023-03-13","arxiv_id":"2303.07489","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-visual-quality-assessment-for-user","title":"Audio-Visual Quality Assessment for User Generated Content: Database and Method","date":"2023-03-04","arxiv_id":"2303.02392","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparative-studies-of-unsupervised-and","title":"Comparative Studies of Unsupervised and Supervised Learning Methods based on Multimedia Applications","date":"2023-03-04","arxiv_id":"2303.02446","repositories_listed":0,"syntology":null},{"url":null,"slug":"saliency-aware-spatio-temporal-artifact","title":"Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment","date":"2023-01-03","arxiv_id":"2301.01069","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-quality-prediction-using-synthetic-and","title":"Image quality prediction using synthetic and natural codebooks: comparative results","date":"2022-12-20","arxiv_id":"2212.10319","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-learning-of-perceptual-video","title":"Semi-supervised Learning of Perceptual Video Quality by Generating Consistent Pairwise Pseudo-Ranks","date":"2022-11-30","arxiv_id":"2211.17075","repositories_listed":0,"syntology":null},{"url":null,"slug":"dcvqe-a-hierarchical-transformer-for-video","title":"DCVQE: A Hierarchical Transformer for Video Quality Assessment","date":"2022-10-10","arxiv_id":"2210.04377","repositories_listed":0,"syntology":null},{"url":"/paper/hvs-revisited-a-comprehensive-video-quality","slug":"hvs-revisited-a-comprehensive-video-quality","title":"HVS Revisited: A Comprehensive Video Quality Assessment Framework","date":"2022-10-09","arxiv_id":"2210.04158","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-human-cognitive-appraisal-through","title":"Learning Human Cognitive Appraisal Through Reinforcement Memory Unit","date":"2022-08-06","arxiv_id":"2208.03473","repositories_listed":0,"syntology":null},{"url":null,"slug":"telepresence-video-quality-assessment","title":"Telepresence Video Quality Assessment","date":"2022-07-20","arxiv_id":"2207.09956","repositories_listed":0,"syntology":null},{"url":null,"slug":"making-video-quality-assessment-models","title":"Making Video Quality Assessment Models Sensitive to Frame Rate Distortions","date":"2022-05-21","arxiv_id":"2205.10501","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-framework-to-map-vmaf-with-the-probability","title":"A Framework to Map VMAF with the Probability of Just Noticeable Difference between Video Encoding Recipes","date":"2022-05-16","arxiv_id":"2205.07565","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-quality-assessment-of-compressed-videos","title":"Deep Quality Assessment of Compressed Videos: A Subjective and Objective Study","date":"2022-05-07","arxiv_id":"2205.03630","repositories_listed":0,"syntology":null},{"url":null,"slug":"perceptual-quality-assessment-of-ugc-gaming","title":"Perceptual Quality Assessment of UGC Gaming Videos","date":"2022-03-31","arxiv_id":"2204.00128","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-mechanisms-inspired-efficient","title":"Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessment","date":"2022-03-28","arxiv_id":"2203.14557","repositories_listed":0,"syntology":null},{"url":null,"slug":"subjective-and-objective-analysis-of-streamed","title":"Subjective and Objective Analysis of Streamed Gaming Videos","date":"2022-03-24","arxiv_id":"2203.12824","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-vqa-based-on-a-novel-hybrid-training","title":"RankDVQA: Deep VQA based on Ranking-inspired Hybrid Training","date":"2022-02-17","arxiv_id":"2202.08595","repositories_listed":0,"syntology":null},{"url":"/paper/locally-adaptive-structure-and-texture","slug":"locally-adaptive-structure-and-texture","title":"Locally Adaptive Structure and Texture Similarity for Image Quality Assessment","date":"2021-10-16","arxiv_id":"2110.08521","repositories_listed":0,"syntology":null},{"url":null,"slug":"prnet-a-progressive-regression-network-for-no","title":"PRNet: A Progressive Regression Network for No-Reference User-Generated-Content Video Quality Assessment","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/high-frame-rate-video-quality-assessment","slug":"high-frame-rate-video-quality-assessment","title":"High Frame Rate Video Quality Assessment using VMAF and Entropic Differences","date":"2021-09-27","arxiv_id":"2109.12785","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-iqa","title":"A survey on IQA","date":"2021-08-29","arxiv_id":"2109.00347","repositories_listed":0,"syntology":null},{"url":null,"slug":"starvqa-space-time-attention-for-video","title":"StarVQA: Space-Time Attention for Video Quality Assessment","date":"2021-08-22","arxiv_id":"2108.09635","repositories_listed":0,"syntology":null},{"url":null,"slug":"fovqa-blind-foveated-video-quality-assessment","title":"FOVQA: Blind Foveated Video Quality Assessment","date":"2021-06-24","arxiv_id":"2106.13328","repositories_listed":0,"syntology":null},{"url":null,"slug":"rich-features-for-perceptual-quality","title":"Rich Features for Perceptual Quality Assessment of UGC Videos","date":"2021-06-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/assessment-of-subjective-and-objective","slug":"assessment-of-subjective-and-objective","title":"Assessment of Subjective and Objective Quality of Live Streaming Sports Videos","date":"2021-06-15","arxiv_id":"2106.08431","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-precision-of-objective-image-video","title":"Improving precision of objective image/video quality metrics","date":"2021-04-26","arxiv_id":"2104.12448","repositories_listed":0,"syntology":null},{"url":null,"slug":"vmaf-and-variants-towards-a-unified-vqa","title":"VMAF And Variants: Towards A Unified VQA","date":"2021-03-13","arxiv_id":"2103.07770","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-vmaf-through-new-feature","title":"Enhancing VMAF through New Feature Integration and Model Combination","date":"2021-03-10","arxiv_id":"2103.06338","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-factor-modeling-of-users-subjective","title":"Latent Factor Modeling of Users Subjective Perception for Stereoscopic 3D Video Recommendation","date":"2021-01-25","arxiv_id":"2101.10039","repositories_listed":0,"syntology":null},{"url":"/paper/capturing-video-frame-rate-variations-through","slug":"capturing-video-frame-rate-variations-through","title":"Capturing Video Frame Rate Variations via Entropic Differencing","date":"2020-06-19","arxiv_id":"2006.11424","repositories_listed":0,"syntology":null}],"record_sha256":"72ecb03ff685321cbbc19f845873ab37d382e9f4b401e6993de16f79d219b9d5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}