相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Unified Quality Assessment of in-the-Wild Videos with Mixed Datasets Training
Dingquan Li et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)
Domain Fingerprints for No-Reference Image Quality Assessment
Weihao Xia et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2021)
Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network
Weixia Zhang et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2020)
Deep Virtual Reality Image Quality Assessment With Human Perception Guider for Omnidirectional Image
Hak Gu Kim et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2020)
Generalizing from a Few Examples: A Survey on Few-shot Learning
Yaqing Wang et al.
ACM COMPUTING SURVEYS (2020)
KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment
Vlad Hosu et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)
Subjective and Objective De-Raining Quality Assessment Towards Authentic Rain Image
Qingbo Wu et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2020)
Perceptual Quality Assessment for Screen Content Images by Spatial Continuity
Yuming Fang et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2020)
End-to-End Blind Image Quality Prediction With Cascaded Deep Neural Network
Jinjian Wu et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)
Deep CNN-Based Blind Image Quality Predictor
Jongyoo Kim et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2019)
Naturalness-Aware Deep No-Reference Image Quality Assessment
Bo Yan et al.
IEEE TRANSACTIONS ON MULTIMEDIA (2019)
Generating Image Distortion Maps Using Convolutional Autoencoders With Application to No Reference Image Quality Assessment
Sathya Veera Reddy Dendi et al.
IEEE SIGNAL PROCESSING LETTERS (2019)
BLIND IMAGE QUALITY ASSESSMENT BY LEARNING FROM MULTIPLE ANNOTATORS
Kede Ma et al.
2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (2019)
On the use of deep learning for blind image quality assessment
Simone Bianco et al.
SIGNAL IMAGE AND VIDEO PROCESSING (2018)
NIMA: Neural Image Assessment
Hossein Talebi et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
Sebastian Bosse et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)
End-to-End Blind Image Quality Assessment Using Deep Neural Networks
Kede Ma et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)
Group Maximum Differentiation Competition: Model Comparison with Few Samples
Kede Ma et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)
Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning
Kwan-Yee Lin et al.
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2018)
Fully Deep Blind Image Quality Predictor
Jongyoo Kim et al.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (2017)
Deep Convolutional Neural Models for Picture-Quality Prediction Challenges and solutions to data-driven image quality assessment
Jongyoo Kim et al.
IEEE SIGNAL PROCESSING MAGAZINE (2017)
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
Kede Ma et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2017)
RankIQA: Learning from Rankings for No-reference Image Quality Assessment
Xialei Liu et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)
Comparison-Based Image Quality Assessment for Selecting Image Restoration Parameters
Haoyi Liang et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)
Blind Image Quality Assessment Based on High Order Statistics Aggregation
Jingtao Xu et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
Deepti Ghadiyaram et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)
Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes
SeyedAlireza Golestaneh et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)
No-Reference Image Blur Assessment Based on Discrete Orthogonal Moments
Leida Li et al.
IEEE TRANSACTIONS ON CYBERNETICS (2016)
CID2013: A Database for Evaluating No-Reference Image Quality Assessment Algorithms
Toni Virtanen et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2015)
A Feature-Enriched Completely Blind Image Quality Evaluator
Lin Zhang et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2015)
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015)
Image database TID2013: Peculiarities, results and perspectives
Nikolay Ponomarenko et al.
SIGNAL PROCESSING-IMAGE COMMUNICATION (2015)
Referenceless Measure of Blocking Artifacts by Tchebichef Kernel Analysis
Leida Li et al.
IEEE SIGNAL PROCESSING LETTERS (2014)
No-Reference Image Quality Assessment in the Spatial Domain
Anish Mittal et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2012)
Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain
Michele A. Saad et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2012)
A Two-Step Framework for Constructing Blind Image Quality Indices
Anush Krishna Moorthy et al.
IEEE SIGNAL PROCESSING LETTERS (2010)
A No-Reference Metric for Perceived Ringing Artifacts in Images
Hantao Liu et al.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2010)
A statistical evaluation of recent full reference image quality assessment algorithms
Hamid Rahim Sheikh et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2006)