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Hekstra, A.P.,
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0401
BibRef
Earlier:
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ICIP02(III: 65-68).
IEEE DOI
0210
BibRef
Earlier: A1, A3, A2:
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ICIP01(II: 89-92).
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0108
BibRef
Lee, D.Y.[Dae Yeol],
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Streaming media, Image coding, Video recording, Quality assessment,
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Streaming media, Video recording, Quality assessment,
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IP(14), No. 11, November 2005, pp. 1928-1942.
IEEE DOI
0510
BibRef
Earlier: A1, A3, A2, A4, A5:
Modelling visual attention and motion effect for visual quality
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ICIP04(IV: 2311-2314).
IEEE DOI
0505
BibRef
Yang, F.Z.[Fu-Zheng],
Wan, S.A.[Shu-Ai],
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A novel objective no-reference metric for digital video quality
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IEEE DOI
0510
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A scalable wavelet-based video distortion metric and applications,
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0604
See also Convex Programming Formulations for Rate Allocation in Video Coding.
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Gu, K.[Ke],
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1502
Gaussian distribution
See also Psychovisual Quality Metric in Free-Energy Principle, A.
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Gu, K.[Ke],
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Visual Saliency Detection With Free Energy Theory,
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1506
filtering theory
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Gu, K.[Ke],
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1507
Brain modeling
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Mei, T.,
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Zhu, C.Z.,
Zhou, H.Q.,
Li, S.,
Home Video Visual Quality Assessment With Spatiotemporal Factors,
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0706
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Chen, J.Y.C.,
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Review of Low Frame Rate Effects on Human Performance,
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Akcakaya, M.,
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Performance of Sparse Representation Algorithms Using Randomly
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Akcakaya, M.,
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Sparse Signal Recovery from a Mixture of Linear and Magnitude-Only
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1503
compressed sensing
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Wang, Z.[Zhou],
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A Technique for Evaluation of CCD Video-Camera Noise,
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0803
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IP(19), No. 2, February 2010, pp. 335-350.
IEEE DOI
1002
BibRef
Earlier:
Unifying Analysis of Full Reference Image Quality Assessment,
ICIP08(1200-1203).
IEEE DOI
0810
See also Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms, A.
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Kim, W.,
Nguyen, A.,
Lee, S.,
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Dynamic Receptive Field Generation for Full-Reference Image Quality
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IEEE DOI
2002
Full-reference image quality assessment (FR-IQA),
dynamic receptive fields (DRFs),
human visual system (HVS)
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Soundararajan, R.,
Bovik, A.C.,
Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic
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IEEE DOI
1304
See also RRED Indices: Reduced Reference Entropic Differencing for Image Quality Assessment.
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Mitra, S.,
Soundararajan, R.,
Channappayya, S.S.,
Predicting Spatio-Temporal Entropic Differences for Robust No
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SPLetters(28), 2021, pp. 170-174.
IEEE DOI
2102
Indexes, Distortion, Streaming media, Quality assessment, Databases,
Video recording, Prediction algorithms,
spatio-temporal reduced reference entropic difference (ST-RRED)
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Moorthy, A.K.,
Seshadrinathan, K.,
Soundararajan, R.,
Bovik, A.C.,
Wireless Video Quality Assessment:
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CirSysVideo(20), No. 4, April 2010, pp. 587-599.
IEEE DOI
1003
BibRef
Moorthy, A.K.,
Bovik, A.C.,
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CirSysVideo(20), No. 11, November 2010, pp. 1653-1658.
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1011
BibRef
Seshadrinathan, K.[Kalpana],
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Bovik, A.C.[Alan C.],
Cormack, L.K.,
Study of Subjective and Objective Quality Assessment of Video,
IP(19), No. 6, June 2010, pp. 1427-1441.
IEEE DOI
1006
BibRef
Min, X.,
Zhai, G.,
Zhou, J.,
Farias, M.C.Q.,
Bovik, A.C.,
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IP(29), 2020, pp. 6054-6068.
IEEE DOI
2005
Streaming media, Distortion, Databases, Quality assessment,
Quality of experience, Video recording, Predictive models,
multimodal fusion
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Yim, C.H.[Chang-Hoon],
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SP:IC(26), No. 1, January 2011, pp. 24-38.
Elsevier DOI
1101
Video communication; Wireless network; Channel error; Quality
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Lee, K.H.[Kwang-Hyun],
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ICIP10(2493-2496).
IEEE DOI
1009
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Garcia, J.A.,
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Martinez-Baena, J.,
Information visibility using transmission methods,
PRL(31), No. 7, 1 May 2010, pp. 609-618.
Elsevier DOI
1004
Computational attention; Transmission; Paradigm; Visual efficiency;
Important information; Advertising
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Nakaguchi, T.[Toshiya],
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Garaj, V.,
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1007
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You, J.Y.[Jun-Yong],
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SP:IC(25), No. 7, August 2010, pp. 482-501.
Elsevier DOI
1008
Survey, Video Quality. Objective quality metric; Subjective quality assessment; HVS;
Psychophysical approach; Engineering approach; Perception; Alignment;
PEAQ; Semantic importance
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You, J.Y.[Jun-Yong],
Perkis, A.,
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EUVIP10(177-182).
IEEE DOI
1110
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Hemami, S.S.[Sheila S.],
Reibman, A.R.[Amy R.],
No-reference image and video quality estimation:
Applications and human-motivated design,
SP:IC(25), No. 7, August 2010, pp. 469-481.
Elsevier DOI
1008
No-reference; Video quality; Quality metrics; Quality estimator;
Applications of quality metrics; Blind quality assessment
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Reibman, A.R.,
Vaishampayan, V.,
Low-Complexity Quality Monitoring of MPEG-2 Video in a Network,
ICIP03(III: 261-264).
IEEE DOI
0312
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Apostolopoulos, J.G.,
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The Challenge of Estimating Video Quality in Video Communication
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SPMag(28), No. 2, 2011, pp. 160-158.
IEEE DOI
1203
[In the Spotlight]
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Do video coding impairments disturb the visual attention deployment?,
SP:IC(25), No. 8, September 2010, pp. 597-609.
Elsevier DOI
1003
BibRef
Earlier: A2, A1, A3, A4:
Does where you Gaze on an Image Affect your Perception of Quality?
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IEEE DOI
0709
Visual attention; Visual quality; Saliency; Video coding; H.264/AVC
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2008
Image color analysis, Fractals, Correlation, Complexity theory,
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1011
Visual quality assessment; Web video; Non-reference; Domain specific
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Huang, Y.H.,
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IEEE DOI
1011
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Yang, F.Z.[Fu-Zheng],
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Xie, Q.,
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Yang, F.Z.[Fu-Zheng],
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1107
See also Lagrange multiplier selection in wavelet-based scalable video coding for quality scalability.
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Huang, S.C.,
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Earlier:
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CRV07(411-417).
IEEE DOI
0705
BibRef
Culibrk, D.,
Mirkovic, M.,
Zlokolica, V.,
Pokric, M.,
Crnojevic, V.,
Kukolj, D.,
Salient Motion Features for Video Quality Assessment,
IP(20), No. 4, April 2011, pp. 948-958.
IEEE DOI
1103
BibRef
Voran, S.[Stephen],
Catellier, A.[Andrew],
Gradient Ascent Subjective Multimedia Quality Testing,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link
1103
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Garcia, M.N.,
Schleicher, R.,
Raake, A.,
Impairment-Factor-Based Audiovisual Quality Model for IPTV:
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JIVP(2011), No. 2011, pp. xx-yy.
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1104
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Wang, Z.[Zhou],
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IP(20), No. 5, May 2011, pp. 1185-1198.
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1104
BibRef
Earlier: A2, A1:
Video Quality Assessment by Incorporating a Motion Perception Model,
ICIP07(II: 173-176).
IEEE DOI
0709
See also Perceptual Image Coding Based on a Maximum of Minimal Structural Similarity Criterion.
BibRef
Hiremath, B.[Basavaraj],
Li, Q.A.[Qi-Ang],
Wang, Z.[Zhou],
Quality-Aware Video,
ICIP07(III: 469-472).
IEEE DOI
0709
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Liu, H.T.[Hao-Ting],
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Discrete quality assessment in IPTV content distribution networks,
SP:IC(26), No. 7, August 2011, pp. 339-357.
Elsevier DOI
1108
IPTV; Quality of experience; Quality assessment; Deep packet inspection
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Lee, J.S.[Jong-Seok],
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1110
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MultMed(16), No. 2, February 2014, pp. 564-571.
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1404
least mean squares methods
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Multimedia Quality Assessment Standards in ITU-T SG12,
SPMag(28), No. 1, 2011, pp. 91-97.
IEEE DOI
1112
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1112
[DSP Forum]
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Park, J.,
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IP(22), No. 2, February 2013, pp. 610-620.
IEEE DOI
1302
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You, J.Y.,
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Perkis, A.,
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1112
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You, J.Y.[Jun-Yong],
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1402
image representation
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Quality of experience in multi-media. Consider the full 3-D data.
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Measure video complexity to get better representation.
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Relate to Shi-Tomasi texture and Harris-Stephens.
See also Combined Corner and Edge Detector, A.
See also integrated background model for video surveillance based on primal sketch and 3D scene geometry, An.
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Scholler, S.,
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1204
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Internet
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Psychometric quality scaling; Maximum likelihood difference scaling;
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CACM(56), No. 3, March 2013, pp. 90.
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With video delivery, it appears that once again "the Internet changes
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As Internet-based videos become mainstream, user expectation for high
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1309
Objective evaluation techniques
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CirSysVideo(23), No. 12, 2013, pp. 2034-2043.
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1312
Analytical models
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IP(22), No. 12, 2013, pp. 5146-5157.
IEEE DOI
1312
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Erratum:
IP(23), No. 1, January 2014, pp. 479-479.
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1402
Biomedical imaging
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Yeh, H.H.[Hsin-Ho],
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Video Aesthetic Quality Assessment by Temporal Integration of Photo-
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MultMed(15), No. 8, December 2013, pp. 1944-1957.
IEEE DOI
1402
feature extraction
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New Image Quality Evaluation Metric for Underwater Video,
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1407
Contrast metric
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Yang, M.,
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An Underwater Color Image Quality Evaluation Metric,
IP(24), No. 12, December 2015, pp. 6062-6071.
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1512
Absorption
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Shahid, M.[Muhammad],
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A Novel No-Reference Video Quality Metric for Evaluating Temporal
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MultMed(17), No. 1, January 2015, pp. 134-139.
IEEE DOI
1502
video signal processing
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Mantel, C.,
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Modeling the Subjective Quality of Highly Contrasted Videos Displayed
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IP(24), No. 2, February 2015, pp. 573-582.
IEEE DOI
1502
image sequences
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Mantel, C.,
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Modeling the Quality of Videos Displayed With Local Dimming Backlight
at Different Peak White and Ambient Light Levels,
IP(25), No. 8, August 2016, pp. 3751-3761.
IEEE DOI
1608
Analysis of variance
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Pinson, M.H.,
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Video Quality Assessment: Subjective testing of entertainment scenes,
SPMag(32), No. 1, January 2015, pp. 101-114.
IEEE DOI
1502
video signal processing
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Torkamani-Azar, F.[Farah],
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Video quality measurement based on 3-D Singular value decomposition,
JVCIR(27), No. 1, 2015, pp. 1-6.
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1502
Image Quality assessment
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Zhu, K.F.[Kong-Feng],
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No-Reference Video Quality Assessment Based on Artifact Measurement
and Statistical Analysis,
CirSysVideo(25), No. 4, April 2015, pp. 533-546.
IEEE DOI
1504
Discrete cosine transforms
BibRef
Zhu, K.F.[Kong-Feng],
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Saupe, D.[Dietmar],
A no-reference video quality assessment based on Laplacian pyramids,
ICIP13(49-53)
IEEE DOI
1402
Databases
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Narwaria, M.[Manish],
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HDR-VQM: An objective quality measure for high dynamic range video,
SP:IC(35), No. 1, 2015, pp. 46-60.
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1506
High dynamic range (HDR) video quality
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Vigier, T.,
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Impact of visual angle on attention deployment and robustness of
visual saliency models in videos: From SD to UHD,
ICIP16(689-693)
IEEE DOI
1610
Computational modeling
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Choi, L.K.[Lark Kwon],
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Motion silencing of flicker distortions on naturalistic videos,
SP:IC(39, Part B), No. 1, 2015, pp. 328-341.
Elsevier DOI
1512
Motion silencing
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Choi, L.K.[Lark Kwon],
Bovik, A.C.[Alan C.],
Flicker sensitive motion tuned video quality assessment,
Southwest16(29-32)
IEEE DOI
1605
Band-pass filters
BibRef
Hameed, A.,
Dai, R.,
Balas, B.,
A Decision-Tree-Based Perceptual Video Quality Prediction Model and
Its Application in FEC for Wireless Multimedia Communications,
MultMed(18), No. 4, April 2016, pp. 764-774.
IEEE DOI
1604
Forward error correction
BibRef
Tuohy, S.[Shane],
Winterlich, A.[Anthony],
McGinley, B.[Brian],
Glavin, M.[Martin],
Jones, E.[Edward],
Denny, P.[Patrick],
Kilmartin, L.[Liam],
Evaluating the influence of packet loss on visual quality of
perception for high bandwidth automotive networks,
SP:IC(43), No. 1, 2016, pp. 15-27.
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1604
Packet loss
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Chen, Z.,
Liao, N.,
Gu, X.,
Wu, F.,
Shi, G.,
Hybrid Distortion Ranking Tuned Bitstream-Layer Video Quality
Assessment,
CirSysVideo(26), No. 6, June 2016, pp. 1029-1043.
IEEE DOI
1606
Degradation
BibRef
Li, X.,
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Lu, X.,
Spatiotemporal Statistics for Video Quality Assessment,
IP(25), No. 7, July 2016, pp. 3329-3342.
IEEE DOI
1606
Distortion
BibRef
Scott, M.J.,
Guntuku, S.C.,
Lin, W.,
Ghinea, G.,
Do Personality and Culture Influence Perceived Video Quality and
Enjoyment?,
MultMed(18), No. 9, September 2016, pp. 1796-1807.
IEEE DOI
1609
cultural aspects
BibRef
Jang, S.,
Lee, J.S.,
On Evaluating Perceptual Quality of Online User-Generated Videos,
MultMed(18), No. 9, September 2016, pp. 1808-1818.
IEEE DOI
1609
Internet
BibRef
Mercer Moss, F.[Felix],
Wang, K.,
Zhang, F.[Fan],
Baddeley, R.[Roland],
Bull, D.R.[David R.],
On the Optimal Presentation Duration for Subjective Video Quality
Assessment,
CirSysVideo(26), No. 11, November 2016, pp. 1977-1987.
IEEE DOI
1609
Context
BibRef
Mercer Moss, F.[Felix],
Yeh, C.T.[Chun-Ting],
Zhang, F.[Fan],
Baddeley, R.[Roland],
Bull, D.R.[David R.],
Support for reduced presentation durations in subjective video
quality assessment,
SP:IC(48), No. 1, 2016, pp. 38-49.
Elsevier DOI
1609
Subjective testing
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Silva, A.F.,
Farias, M.C.Q.[Mylène C.Q.],
Redi, J.A.,
Perceptual Annoyance Models for Videos With Combinations of Spatial
and Temporal Artifacts,
MultMed(18), No. 12, December 2016, pp. 2446-2456.
IEEE DOI
1612
Codecs
BibRef
Farias, M.C.Q.,
Mitra, S.K.,
No-Reference Video Quality Metric Based on Artifact Measurements,
ICIP05(III: 141-144).
IEEE DOI
0512
BibRef
Podder, P.K.[Pallab Kanti],
Paul, M.[Manoranjan],
Murshed, M.[Manzur],
QMET: A new quality assessment metric for no-reference video coding
by using human eye traversal,
ICVNZ16(1-6)
IEEE DOI
1701
Correlation
BibRef
Guo, J.F.[Jie-Feng],
Hu, G.[Gong],
Xu, W.J.[Wei-Jian],
Huang, L.F.[Lian-Fen],
Hierarchical content importance-based video quality assessment for
HEVC encoded videos transmitted over LTE networks,
JVCIR(43), No. 1, 2017, pp. 50-60.
Elsevier DOI
1702
Content type
BibRef
Zhang, W.,
Liu, H.,
Study of Saliency in Objective Video Quality Assessment,
IP(26), No. 3, March 2017, pp. 1275-1288.
IEEE DOI
1703
distortion
BibRef
Song, J.,
Yang, F.,
Zhou, Y.,
Gao, S.,
Parametric Planning Model for Video Quality Evaluation of IPTV
Services Combining Channel and Video Characteristics,
MultMed(19), No. 5, May 2017, pp. 1015-1029.
IEEE DOI
1704
Distortion
BibRef
Vega, M.T.,
Mocanu, D.C.,
Famaey, J.,
Stavrou, S.,
Liotta, A.,
Deep Learning for Quality Assessment in Live Video Streaming,
SPLetters(24), No. 6, June 2017, pp. 736-740.
IEEE DOI
1705
unsupervised learning, video signal processing, video streaming,
FR benchmark, LIMP Video Quality Database,
extensive packet loss impaired video set,
inexpensive no-reference measurements,
offline deep unsupervised learning processes, online analysis,
quality assessment methods, real-time analysis,
real-time assessment, video assessment method,
video content providers, video quality metric,
Feature extraction, Machine learning, Measurement,
Quality assessment, Real-time systems, Streaming media,
Video recording, Deep learning (DL), multimedia video services,
unsupervised learning (UL), video, quality, assessment
BibRef
Peng, P.[Peng],
Liao, D.P.[Dan-Ping],
Li, Z.N.[Ze-Nian],
An efficient temporal distortion measure of videos based on spacetime
texture,
PR(70), No. 1, 2017, pp. 1-11.
Elsevier DOI
1706
Video, quality, assessment
BibRef
Wang, H.Q.[Hai-Qiang],
Katsavounidis, I.[Ioannis],
Zhou, J.T.[Jian-Tong],
Park, J.[Jeonghoon],
Lei, S.[Shawmin],
Zhou, X.[Xin],
Pun, M.O.[Man-On],
Jin, X.[Xin],
Wang, R.G.[Rong-Gang],
Wang, X.[Xu],
Zhang, Y.[Yun],
Huang, J.W.[Ji-Wu],
Kwong, S.[Sam],
Kuo, C.C.J.[C.C. Jay],
VideoSet: A large-scale compressed video quality dataset based on JND
measurement,
JVCIR(46), No. 1, 2017, pp. 292-302.
Elsevier DOI
1706
Human visual system (HVS)
BibRef
Al-Naji, A.[Ali],
Lee, S.H.[Sang-Heon],
Chahl, J.[Javaan],
Quality index evaluation of videos based on fuzzy interface system,
IET-IPR(11), No. 5, April 2017, pp. 292-300.
DOI Link
1706
BibRef
Sun, Y.,
Lu, A.,
Yu, L.,
Weighted-to-Spherically-Uniform Quality Evaluation for
Omnidirectional Video,
SPLetters(24), No. 9, September 2017, pp. 1408-1412.
IEEE DOI
1708
Distortion, Distortion measurement,
Extraterrestrial measurements, Measurement uncertainty, Weight measurement,
Objective quality evaluation, omnidirectional video, projection format
BibRef
Sun, Y.,
Yu, L.,
Coding optimization based on weighted-to-spherically-uniform quality
metric for 360 video,
VCIP17(1-4)
IEEE DOI
1804
distortion, quantisation (signal), video coding, CMP, CTU level,
CTU position, ERP, WS-PSNR weights, adaptive quantization method,
weighted quality
BibRef
Hu, S.,
Jin, L.,
Wang, H.,
Zhang, Y.,
Kwong, S.,
Kuo, C.C.J.,
Objective Video Quality Assessment Based on Perceptually Weighted
Mean Squared Error,
CirSysVideo(27), No. 9, September 2017, pp. 1844-1855.
IEEE DOI
1709
Distortion, Distortion measurement, Quality assessment,
Sensitivity, Video recording, Visualization,
Human visual system (HVS),
BibRef
Bosse, S.,
Maniry, D.,
Müller, K.R.,
Wiegand, T.,
Samek, W.,
Deep Neural Networks for No-Reference and Full-Reference Image
Quality Assessment,
IP(27), No. 1, January 2018, pp. 206-219.
IEEE DOI
1712
feature extraction, image colour analysis,
learning (artificial intelligence), neural nets,
regression
BibRef
Ndjiki-Nya, P.[Patrick],
Barrado, M.[Mikel],
Wiegand, T.[Thomas],
Efficient Full-Reference Assessment of Image and Video Quality,
ICIP07(II: 125-128).
IEEE DOI
0709
BibRef
Zou, W.J.[Wen-Jie],
Yang, F.Z.[Fu-Zheng],
Wan, S.[Shuai],
Perceptual video quality metric for compression artefacts: from
two-dimensional to omnidirectional,
IET-IPR(12), No. 3, March 2018, pp. 374-381.
DOI Link
1802
BibRef
Hatchett, J.[Jonathan],
Debattista, K.[Kurt],
Mukherjee, R.[Ratnajit],
Bashford-Rogers, T.[Thomas],
Chalmers, A.[Alan],
An evaluation of power transfer functions for HDR video compression,
VC(34), No. 2, February 2018, pp. 167-176.
Springer DOI
1802
BibRef
Freitas, P.G.[Pedro Garcia],
Akamine, W.Y.L.[Welington Y.L.],
Farias, M.C.Q.[Mylène C.Q.],
Using multiple spatio-temporal features to estimate video quality,
SP:IC(64), 2018, pp. 1-10.
Elsevier DOI
1804
Video quality assessment, Texture operator,
Spatio-temporal texture analysis, Machine learning, Random forest regression
BibRef
Akamine, W.Y.L.[Welington Y.L.],
Freitas, P.G.[Pedro Garcia],
Farias, M.C.Q.[Mylène C.Q.],
A framework for computationally efficient video quality assessment,
SP:IC(70), 2019, pp. 57-67.
Elsevier DOI
1812
Video quality assessment methods, Spatial resolution, Runtime performance
BibRef
Choi, L.K.[Lark Kwon],
Bovik, A.C.[Alan Conrad],
Video quality assessment accounting for temporal visual masking of
local flicker,
SP:IC(67), 2018, pp. 182-198.
Elsevier DOI
1808
Video quality assessment, Temporal visual masking,
Motion silencing, Flicker visibility, Human visual system
BibRef
Narwaria, M.,
Krasula, L.,
Le Callet, P.[Patrick],
Data Analysis in Multimedia Quality Assessment:
Revisiting the Statistical Tests,
MultMed(20), No. 8, August 2018, pp. 2063-2072.
IEEE DOI
1808
data analysis, multimedia communication, statistical testing,
data analysis, multimedia quality assessment, objective methods,
statistical analysis
BibRef
Ghadiyaram, D.,
Pan, J.,
Bovik, A.C.,
Moorthy, A.K.,
Panda, P.,
Yang, K.,
In-Capture Mobile Video Distortions:
A Study of Subjective Behavior and Objective Algorithms,
CirSysVideo(28), No. 9, September 2018, pp. 2061-2077.
IEEE DOI
1809
Distortion, Databases, Cameras, Quality assessment, Video recording,
Mobile communication, Mobile handsets, Mobile videos,
smart-phone cameras
BibRef
Sinno, Z.[Zeina],
Bovik, A.C.[Alan C.],
Large-Scale Study of Perceptual Video Quality,
IP(28), No. 2, February 2019, pp. 612-627.
IEEE DOI
1811
BibRef
Earlier:
Large Scale Subjective Video Quality Study,
ICIP18(276-280)
IEEE DOI
1809
cameras, data compression, image capture, video coding,
video databases, video recording, video signal processing,
multimedia.
Distortion, Browsers,
Training, Testing, Video Quality Assessment, Subjective Study, Crowdsourcing
BibRef
Sinno, Z.,
Moorthy, A.K.,
de Cock, J.,
Li, Z.,
Bovik, A.C.,
Quality Measurement of Images on Mobile Streaming Interfaces Deployed
at Scale,
IP(29), 2020, pp. 2536-2551.
IEEE DOI
2001
Streaming media, Databases, Distortion, Visualization, Image coding,
Transform coding, Image quality assessment (IQA), mobile streaming
BibRef
Singh, R.[Ranjit],
Aggarwal, N.[Naveen],
A distortion-agnostic video quality metric based on multi-scale
spatio-temporal structural information,
SP:IC(74), 2019, pp. 299-308.
Elsevier DOI
1904
Video quality assessment (VQA), No-reference (NR),
Local binary patterns (LBP), Three orthogonal planes (TOP),
Video quality dataset
BibRef
Aldahdooh, A.[Ahmed],
Masala, E.[Enrico],
van Wallendael, G.[Glenn],
Lambert, P.[Peter],
Barkowsky, M.[Marcus],
Improving relevant subjective testing for validation: Comparing
machine learning algorithms for finding similarities in VQA datasets
using objective measures,
SP:IC(74), 2019, pp. 32-41.
Elsevier DOI
1904
Subjective testing, Subset selection, Statistical analysis,
Video quality assessment, Clustering
BibRef
Shang, X.,
Liang, J.,
Wang, G.,
Zhao, H.,
Wu, C.,
Lin, C.,
Color-Sensitivity-Based Combined PSNR for Objective Video Quality
Assessment,
CirSysVideo(29), No. 5, May 2019, pp. 1239-1250.
IEEE DOI
1905
Sensitivity, Color, Encoding, Quality assessment, Visualization,
Video recording, Video quality assessment, color sensitivity, PSNR,
visual sensitivity
BibRef
Aldahdooh, A.,
Masala, E.,
Janssens, O.,
van Wallendael, G.,
Barkowsky, M.,
Le Callet, P.[Patrick],
Improved Performance Measures for Video Quality Assessment Algorithms
Using Training and Validation Sets,
MultMed(21), No. 8, August 2019, pp. 2026-2041.
IEEE DOI
1908
image sequences, learning (artificial intelligence), set theory,
video signal processing, performance measures,
content features
BibRef
Bampis, C.G.,
Li, Z.,
Bovik, A.C.,
Spatiotemporal Feature Integration and Model Fusion for Full
Reference Video Quality Assessment,
CirSysVideo(29), No. 8, August 2019, pp. 2256-2270.
IEEE DOI
1908
Streaming media, Quality assessment, Video recording,
Feature extraction, Distortion measurement,
VMAF
BibRef
Zhang, Y.,
Gao, X.,
He, L.,
Lu, W.,
He, R.,
Blind Video Quality Assessment With Weakly Supervised Learning and
Resampling Strategy,
CirSysVideo(29), No. 8, August 2019, pp. 2244-2255.
IEEE DOI
1908
Measurement, Feature extraction, Quality assessment,
Spatiotemporal phenomena, Streaming media, Video recording,
resampling
BibRef
Heng, W.,
Jiang, T.,
Gao, W.,
How to Assess the Quality of Compressed Surveillance Videos Using
Face Recognition,
CirSysVideo(29), No. 8, August 2019, pp. 2229-2243.
IEEE DOI
1908
Face, Surveillance, Task analysis, Face recognition,
Feature extraction, Quality assessment, Video recording,
face recognition
BibRef
Papadopoulos, M.A.[Miltiadis Alexios],
Katsenou, A.V.[Angeliki V.],
Agrafiotis, D.[Dimitris],
Bull, D.R.[David R.],
A multi-metric approach for block-level video quality assessment,
SP:IC(78), 2019, pp. 152-158.
Elsevier DOI
1909
Video quality assessment, Content features, Fusion of metrics,
Block-level, RDO
BibRef
Vranješ, M.[Mario],
Bajcinovci, V.[Viliams],
Grbic, R.[Ratko],
Vajak, D.[Denis],
No-reference artifacts measurements based video quality metric,
SP:IC(78), 2019, pp. 345-358.
Elsevier DOI
1909
AMB-VQM, Video quality assessment, No-reference,
Video artifacts, Video quality database
BibRef
Athar, S.,
Costa, T.,
Zeng, K.,
Wang, Z.,
Perceptual Quality Assessment of UHD-HDR-WCG Videos,
ICIP19(1740-1744)
IEEE DOI
1910
video quality assessment, high dynamic range, wide color gamut,
ultra high definition, 4K, subjective testing,
objective analysis
BibRef
Oh, S.R.,
Jeong, S.,
Heo, P.,
Kim, D.,
Kim, H.Y.,
Park, H.,
A New No-Reference Method for Judder Artifact Assessment,
CirSysVideo(29), No. 10, October 2019, pp. 2888-2898.
IEEE DOI
1910
image motion analysis, image sequences, motion compensation,
regression analysis, video signal processing, visual perception,
subjective assessment
BibRef
Korhonen, J.,
Two-Level Approach for No-Reference Consumer Video Quality Assessment,
IP(28), No. 12, December 2019, pp. 5923-5938.
IEEE DOI
1909
Video recording, Quality assessment, Streaming media,
Feature extraction, Distortion, Image coding, Databases,
quality management
BibRef
You, J.,
Korhonen, J.,
Deep Neural Networks for No-Reference Video Quality Assessment,
ICIP19(2349-2353)
IEEE DOI
1910
3D-CNN, deep learning, LSTM, video quality assessment
BibRef
Mustafa, S.[Safi],
Hameed, A.[Abdul],
Perceptual quality assessment of video using machine learning algorithm,
SIViP(13), No. 8, November 2019, pp. 1495-1502.
WWW Link.
1911
BibRef
Varga, D.[Domonkos],
Szirányi, T.[Tamás],
No-reference video quality assessment via pretrained CNN and LSTM
networks,
SIViP(13), No. 8, November 2019, pp. 1569-1576.
WWW Link.
1911
BibRef
Varga, D.[Domonkos],
Composition-preserving deep approach to full-reference image quality
assessment,
SIViP(14), No. 6, September 2020, pp. 1265-1272.
WWW Link.
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BibRef
Yuan, Y.[Ying],
Wang, C.[Cong],
IPTV video quality assessment model based on neural network,
JVCIR(64), 2019, pp. 102629.
Elsevier DOI
1911
BP neural network, IPTV video, Quality assessment, Clustering analysis
BibRef
Wu, J.,
Liu, Y.,
Dong, W.,
Shi, G.,
Lin, W.,
Quality Assessment for Video With Degradation Along Salient
Trajectories,
MultMed(21), No. 11, November 2019, pp. 2738-2749.
IEEE DOI
1911
Trajectory, Degradation, Motion measurement,
Distortion measurement, Optical distortion, Distortion,
spatial-temporal quality degradation
BibRef
Kulupana, G.,
Talagala, D.S.,
Arachchi, H.K.,
Fernando, A.,
End User Video Quality Prediction and Coding Parameters Selection at
the Encoder for Robust HEVC Video Transmission,
CirSysVideo(29), No. 11, November 2019, pp. 3367-3381.
IEEE DOI
1911
Distortion, Encoding, Decoding, Video recording, Quality assessment,
Video coding, Prediction algorithms, HEVC,
error concealment
BibRef
Xu, M.,
Li, C.,
Chen, Z.,
Wang, Z.,
Guan, Z.,
Assessing Visual Quality of Omnidirectional Videos,
CirSysVideo(29), No. 12, December 2019, pp. 3516-3530.
IEEE DOI
1912
Videos, Measurement, Visualization, viewing direction
Video coding, Databases, Distortion, Omnidirectional video coding,
BibRef
Rohil, M.K.[Mukesh Kumar],
Gupta, N.[Neetika],
Yadav, P.[Prakash],
An improved model for no-reference image quality assessment and a
no-reference video quality assessment model based on frame analysis,
SIViP(14), No. 1, February 2020, pp. 205-213.
WWW Link.
2001
BibRef
Liu, L.X.[Li-Xiong],
Wang, T.S.[Tian-Shu],
Huang, H.[Hua],
Bovik, A.C.[Alan Conrad],
Video quality assessment using space-time slice mappings,
SP:IC(82), 2020, pp. 115749.
Elsevier DOI
2001
Video quality assessment, Image quality assessment,
Spatial temporal slice, Space-time stability, Learning based pooling
BibRef
Zheng, Q.[Qi],
Tu, Z.Z.[Zheng-Zhong],
Hao, Z.J.[Zhi-Jian],
Zeng, X.Y.[Xiao-Yang],
Bovik, A.C.[Alan C.],
Fan, Y.[Yibo],
Blind Video Quality Assessment via Space-Time Slice Statistics,
ICIP22(451-455)
IEEE DOI
2211
Codes, Statistical analysis, Databases, User-generated content,
Predictive models, Feature extraction, Distortion,
user-generated content
BibRef
Ebenezer, J.P.[Joshua Peter],
Shang, Z.X.[Zai-Xi],
Wu, Y.J.[Yong-Jun],
Wei, H.[Hai],
Sethuraman, S.[Sriram],
Bovik, A.C.[Alan C.],
ChipQA: No-Reference Video Quality Prediction via Space-Time Chips,
IP(30), 2021, pp. 8059-8074.
IEEE DOI
2109
Quality assessment, Video recording, Prediction algorithms,
Optical distortion, Visualization, Distortion, Databases,
human visual system
BibRef
Jin, Y.Z.[Yi-Ze],
Patney, A.[Anjul],
Webb, R.[Richard],
Bovik, A.C.[Alan C.],
FOVQA: Blind Foveated Video Quality Assessment,
IP(31), 2022, pp. 4571-4584.
IEEE DOI
2207
Quality assessment, Predictive models, Video recording, Distortion,
Solid modeling, Feature extraction, Visualization,
virtual reality
BibRef
Jin, Y.Z.[Yi-Ze],
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ICIP21(1419-1423)
IEEE DOI
2201
Solid modeling, Stacking, Virtual reality, Streaming media,
Video compression, Nonuniform sampling, Retina, foveation,
virtual reality
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The Performance of Quality Metrics in Assessing Error-Concealed Video
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2005
Error/loss concealment, video quality assessment, image quality assessment
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2005
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Lin, L.,
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CirSysVideo(30), No. 11, November 2020, pp. 3898-3910.
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2011
Video coding, Databases, Encoding, Image color analysis,
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H265/HEVC
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Ling, S.,
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Quality Assessment of Free-Viewpoint Videos by Quantifying the
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IEEE DOI
2012
Distortion, Measurement, Trajectory, Videos, Quality assessment,
Strain, Shape, Free-viewpoint video, free-viewpoint TV,
video quality assessment
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Semantic Information Oriented No-Reference Video Quality Assessment,
SPLetters(28), 2021, pp. 204-208.
IEEE DOI
2102
Feature extraction, Semantics, Distortion, Quality assessment,
Data mining, Video recording, Degradation,
low-level features
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Yang, J.C.[Jia-Chen],
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MultMed(23), 2021, pp. 797-809.
IEEE DOI
2102
convolutional neural nets, stereo image processing,
video retrieval, video signal processing, virtual reality,
spatiotemporal information
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Unified Quality Assessment of in-the-Wild Videos with Mixed Datasets
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Springer DOI
2104
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Qian, L.,
Pan, T.,
Zheng, Y.,
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Yu, B.,
Wang, B.,
No-Reference Nonuniform Distorted Video Quality Assessment Based on
Deep Multiple Instance Learning,
MultMedMag(28), No. 1, January 2021, pp. 28-37.
IEEE DOI
2104
Feature extraction, Quality assessment, Distortion, Reliability,
Video recording, Training, No reference, Video quality assessment,
Multiple instance learning
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IP(30), 2021, pp. 4449-4464.
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2104
Databases, Quality assessment, Video recording, Streaming media,
Distortion, Image coding, Feature extraction,
user-generated content
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Yu, X.X.[Xiang-Xu],
Tu, Z.Z.[Zheng-Zhong],
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Wang, Y.L.[Yi-Lin],
Adsumilli, B.[Balu],
Subjective Quality Assessment of User-Generated Content Gaming Videos,
VAQuality22(74-83)
IEEE DOI
2202
Industries, Analytical models, Databases,
Conferences, User-generated content, Games
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Saha, A.[Avinab],
Chen, Y.C.[Yu-Chih],
Davis, C.[Chase],
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Study of Subjective and Objective Quality Assessment of Mobile Cloud
Gaming Videos,
IP(32), 2023, pp. 3295-3310.
IEEE DOI
2307
Videos, Cloud gaming, Databases, Quality assessment, Data models,
Video games, Industries, Mobile cloud gaming,
cloud gaming video quality database
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Tu, Z.Z.[Zheng-Zhong],
Chen, C.J.,
Chen, L.H.,
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A Comparative Evaluation Of Temporal Pooling Methods For Blind Video
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ICIP20(141-145)
IEEE DOI
2011
Video recording, Quality assessment, Hysteresis, Streaming media,
Predictive models, Databases, Harmonic analysis, temporal visual masking
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Oppong Bediako, D.[Daniel],
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Joint model of gradient magnitude and Gabor features via
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JVCIR(79), 2021, pp. 103204.
Elsevier DOI
2109
Full-reference (FR) video quality assessment,
Gradient magnitude, Gabor filter
BibRef
Madhusudana, P.C.[Pavan C.],
Birkbeck, N.[Neil],
Wang, Y.L.[Yi-Lin],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate
Dependent Video Quality Prediction,
IP(30), 2021, pp. 7446-7457.
IEEE DOI
2109
Video recording, Quality assessment, Streaming media, Databases,
Band-pass filters, Predictive models, Distortion, High frame rate,
generalized Gaussian distribution
BibRef
Yu, X.X.[Xiang-Xu],
Birkbeck, N.[Neil],
Wang, Y.L.[Yi-Lin],
Bampis, C.G.[Christos G.],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
Predicting the Quality of Compressed Videos With Pre-Existing
Distortions,
IP(30), 2021, pp. 7511-7526.
IEEE DOI
2109
Videos, Predictive models, Image coding, Databases,
Nonlinear distortion, Quality assessment, Computational modeling,
user-generated-content
BibRef
Sun, T.F.[Tong-Feng],
Ding, S.F.[Shi-Fei],
Chen, W.[Wei],
Blind video quality assessment based on multilevel video perception,
SP:IC(99), 2021, pp. 116485.
Elsevier DOI
2111
Blind video quality assessment, Natural video statistics,
Motion features, Feature fusion, Video enhancement
BibRef
Kancharla, P.[Parimala],
Channappayya, S.S.[Sumohana S.],
Completely Blind Quality Assessment of User Generated Video Content,
IP(31), 2022, pp. 263-274.
IEEE DOI
2112
Feature extraction, Quality assessment, Computational modeling,
Video recording, Prediction algorithms, Predictive models,
video quality assessment (VQA)
BibRef
Chen, P.F.[Peng-Fei],
Li, L.D.[Lei-Da],
Wu, J.J.[Jin-Jian],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
Contrastive Self-Supervised Pre-Training for Video Quality Assessment,
IP(31), 2022, pp. 458-471.
IEEE DOI
2112
Task analysis, Distortion, Predictive models, Quality assessment,
Manuals, Data models, Streaming media, Video quality assessment,
distortion augmentation
BibRef
Gao, P.[Pan],
Zhang, P.W.[Peng-Wei],
Smolic, A.[Aljosa],
Quality Assessment for Omnidirectional Video:
A Spatio-Temporal Distortion Modeling Approach,
MultMed(24), 2022, pp. 1-16.
IEEE DOI
2202
Measurement, Distortion, Quality assessment, Video recording,
Visualization, Distortion measurement,
spatio-temporal distortion
BibRef
Luo, D.[Dengyan],
Ye, M.[Mao],
Li, S.[Shuai],
Li, X.[Xue],
Coarse-to-Fine Spatio-Temporal Information Fusion for Compressed
Video Quality Enhancement,
SPLetters(29), 2022, pp. 543-547.
IEEE DOI
2202
Convolution, Feature extraction, Training, Video recording,
Quality assessment, Fuses, 3D convolution, deformable convolution,
quality enhancement
BibRef
Luo, D.[Dengyan],
Ye, M.[Mao],
Li, S.[Shuai],
Zhu, C.[Ce],
Li, X.[Xue],
Spatio-Temporal Detail Information Retrieval for Compressed Video
Quality Enhancement,
MultMed(25), 2023, pp. 6808-6820.
IEEE DOI
2311
BibRef
Wang, Z.Y.[Ze-Yang],
Ye, M.[Mao],
Li, S.[Shuai],
Li, X.[Xue],
Multi-Frame Compressed Video Quality Enhancement by Spatio-Temporal
Information Balance,
SPLetters(30), 2023, pp. 105-109.
IEEE DOI
2303
Feature extraction, Convolution, Signal processing algorithms,
Encoding, Computational modeling, Image coding, spatio-temporal information
BibRef
Wang, G.C.[Guang-Cheng],
Wang, Z.Y.[Zhong-Yuan],
Gu, K.[Ke],
Jiang, K.[Kui],
He, Z.[Zheng],
Reference-Free DIBR-Synthesized Video Quality Metric in Spatial and
Temporal Domains,
CirSysVideo(32), No. 3, March 2022, pp. 1119-1132.
IEEE DOI
2203
Optical distortion, Distortion measurement, Quality assessment,
Nonlinear distortion, Optical imaging, Integrated optics,
spatial and temporal domains
BibRef
Madhusudana, P.C.[Pavan C.],
Birkbeck, N.[Neil],
Wang, Y.L.[Yi-Lin],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
Making Video Quality Assessment Models Sensitive to Frame Rate
Distortions,
SPLetters(29), No. 2022, pp. 897-901.
IEEE DOI
2204
Streaming media, Predictive models, Entropy, Band-pass filters,
Video recording, Quality assessment, Rate-distortion,
feature fusion
BibRef
Ebenezer, J.P.[Joshua P.],
Shang, Z.X.[Zai-Xi],
Wu, Y.J.[Yong-Jun],
Wei, H.[Hai],
Sethuraman, S.[Sriram],
Bovik, A.C.[Alan C.],
Making Video Quality Assessment Models Robust to Bit Depth,
SPLetters(30), 2023, pp. 488-492.
IEEE DOI
2305
Databases, Feature extraction, Predictive models,
Prediction algorithms, Nonlinear distortion, Dynamic range,
video quality assessment
BibRef
Otroshi-Shahreza, H.[Hatef],
Amini, A.[Arash],
Behroozi, H.[Hamid],
Feature-based no-reference video quality assessment using Extra Trees,
IET-IPR(16), No. 6, 2022, pp. 1531-1543.
DOI Link
2204
BibRef
Chen, B.L.[Bao-Liang],
Zhu, L.Y.[Ling-Yu],
Li, G.[Guo],
Lu, F.B.[Fang-Bo],
Fan, H.F.[Hong-Fei],
Wang, S.Q.[Shi-Qi],
Learning Generalized Spatial-Temporal Deep Feature Representation for
No-Reference Video Quality Assessment,
CirSysVideo(32), No. 4, April 2022, pp. 1903-1916.
IEEE DOI
2204
Feature extraction, Quality assessment, Training, Video recording,
Image quality, Streaming media, Nonlinear distortion,
temporal aggregation
BibRef
Liu, Y.X.[Yong-Xu],
Wu, J.J.[Jin-Jian],
Li, L.[Leida],
Dong, W.S.[Wei-Sheng],
Zhang, J.P.[Jin-Peng],
Shi, G.M.[Guang-Ming],
Spatiotemporal Representation Learning for Blind Video Quality
Assessment,
CirSysVideo(32), No. 6, June 2022, pp. 3500-3513.
IEEE DOI
2206
Feature extraction, Spatiotemporal phenomena, Databases,
Quality assessment, Video recording, Data models, Task analysis,
weakly supervised learning
BibRef
Liu, Y.X.[Yong-Xu],
Wu, J.J.[Jin-Jian],
Li, A.[Aobo],
Li, L.[Leida],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
Lin, W.S.[Wei-Si],
Video Quality Assessment With Serial Dependence Modeling,
MultMed(24), 2022, pp. 3754-3768.
IEEE DOI
2208
Degradation, Data mining, Video Quality Assessment,
Serial Dependence, Long-Short Term Memory, Attention
BibRef
Li, B.[Bowen],
Zhang, W.X.[Wei-Xia],
Tian, M.[Meng],
Zhai, G.T.[Guang-Tao],
Wang, X.[Xianpei],
Blindly Assess Quality of In-the-Wild Videos via Quality-Aware
Pre-Training and Motion Perception,
CirSysVideo(32), No. 9, September 2022, pp. 5944-5958.
IEEE DOI
2209
Videos, Feature extraction, Databases, Distortion, Training,
Quality assessment, Blind video quality assessment, in-the-wild videos
BibRef
Dziembowski, A.[Adrian],
Mieloch, D.[Dawid],
Stankowski, J.[Jakub],
Grzelka, A.[Adam],
IV-PSNR: The Objective Quality Metric for Immersive Video
Applications,
CirSysVideo(32), No. 11, November 2022, pp. 7575-7591.
IEEE DOI
2211
Measurement, Image color analysis, Distortion, Cameras, Navigation,
Image coding, Media, Image quality, immersive video,
view synthesis
BibRef
Vishwakarma, A.K.[Anish Kumar],
Bhurchandi, K.M.[Kishor M.],
No-Reference Video Quality Assessment using novel hybrid features and
two-stage hybrid regression for score level fusion,
JVCIR(89), 2022, pp. 103676.
Elsevier DOI
2212
Human visual system, No-reference video quality assessment,
3D steerable DWT, Perceptual features, User generated content,
Support vector regression
BibRef
Zheng, Q.[Qi],
Tu, Z.Z.[Zheng-Zhong],
Zeng, X.Y.[Xiao-Yang],
Bovik, A.C.[Alan C.],
Fan, Y.[Yibo],
A Completely Blind Video Quality Evaluator,
SPLetters(29), 2022, pp. 2228-2232.
IEEE DOI
2212
Video recording, Quality assessment, Feature extraction,
Computational modeling, Streaming media, Distortion, linear model
BibRef
Cao, L.[Lina],
Guo, D.L.[Dong-Liang],
Wang, Q.[Quan],
Feng, L.[Li],
Shi, C.[Chuanbao],
Video Quality Assessment of Danmaku-Based Video Saliency Regions,
SPLetters(29), 2022, pp. 2213-2217.
IEEE DOI
2212
Quality assessment, Visualization, Video recording,
Sentiment analysis, Saliency detection, Image color analysis,
Pearson correlation coefficient
BibRef
Yang, L.[Li],
Xu, M.[Mai],
Li, S.X.[Sheng-Xi],
Guo, Y.C.[Yi-Chen],
Wang, Z.[Zulin],
Blind VQA on 360° Video via Progressively Learning From Pixels,
Frames, and Video,
IP(32), 2023, pp. 128-143.
IEEE DOI
2301
Task analysis, Degradation, Quality assessment, Distortion,
Visualization, Convolutional neural networks, Image coding,
progressively learning
BibRef
Li, Y.[Yang],
Meng, S.B.[Sheng-Bin],
Zhang, X.F.[Xin-Feng],
Wang, M.[Meng],
Wang, S.Q.[Shi-Qi],
Wang, Y.[Yue],
Ma, S.W.[Si-Wei],
User-Generated Video Quality Assessment:
A Subjective and Objective Study,
MultMed(25), 2023, pp. 154-166.
IEEE DOI
2301
Quality assessment, Distortion, Video recording, Databases,
Feature extraction, Convolutional neural networks,
video quality assessment
BibRef
Zhu, H.W.[Han-Wei],
Chen, B.L.[Bao-Liang],
Zhu, L.Y.[Ling-Yu],
Wang, S.Q.[Shi-Qi],
Learning Spatiotemporal Interactions for User-Generated Video Quality
Assessment,
CirSysVideo(33), No. 3, March 2023, pp. 1031-1042.
IEEE DOI
2303
Distortion, Transformers, Feature extraction,
Spatiotemporal phenomena, Video recording, Quality assessment,
vision transformer
BibRef
Zhu, H.W.[Han-Wei],
Chen, B.L.[Bao-Liang],
Zhu, L.Y.[Ling-Yu],
Chen, P.L.[Pei-Lin],
Song, L.Q.[Lin-Qi],
Wang, S.Q.[Shi-Qi],
Video Quality Assessment for Spatio-Temporal Resolution Adaptive
Coding,
CirSysVideo(34), No. 7, July 2024, pp. 6403-6415.
IEEE DOI Code:
WWW Link.
2407
Adaptation models, Quality assessment, Spatial resolution,
Bit rate, Video recording, Encoding, Feature extraction,
vision transformer
BibRef
Liu, Y.X.[Yong-Xu],
Wu, J.J.[Jin-Jian],
Li, L.[Leida],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
Quality Assessment of UGC Videos Based on Decomposition and
Recomposition,
CirSysVideo(33), No. 3, March 2023, pp. 1043-1054.
IEEE DOI
2303
Dynamics, Videos, Degradation, Task analysis, Quality assessment,
Streaming media, User-Generated Content,
progressive aggregation
BibRef
Cao, Y.Q.[Yu-Qin],
Min, X.K.[Xiong-Kuo],
Sun, W.[Wei],
Zhai, G.T.[Guang-Tao],
Attention-Guided Neural Networks for Full-Reference and No-Reference
Audio-Visual Quality Assessment,
IP(32), 2023, pp. 1882-1896.
IEEE DOI
2303
BibRef
Earlier:
Deep Neural Networks for Full-Reference and No-Reference Audio-Visual
Quality Assessment,
ICIP21(1429-1433)
IEEE DOI
2201
Feature extraction, Visualization, Quality assessment, Measurement,
Streaming media, Video recording, multimodal fusion.
Deep learning, Databases, Fuses, Logic gates, Audio-visual quality assessment,
multimodal fusion
BibRef
Chen, Y.C.[Yu-Chih],
Saha, A.[Avinab],
Davis, C.[Chase],
Qiu, B.[Bo],
Wang, X.M.[Xiao-Ming],
Gowda, R.[Rahul],
Katsavounidis, I.[Ioannis],
Bovik, A.C.[Alan C.],
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content,
SPLetters(30), 2023, pp. 324-328.
IEEE DOI
2304
Streaming media, Feature extraction, Computational modeling,
Quality assessment, Video recording, Predictive models, temporal statistics
BibRef
Fang, Y.M.[Yu-Ming],
Li, Z.Q.[Zhao-Qian],
Yan, J.[Jiebin],
Sui, X.J.[Xiang-Jie],
Liu, H.T.[Han-Tao],
Study of Spatio-Temporal Modeling in Video Quality Assessment,
IP(32), 2023, pp. 2693-2702.
IEEE DOI
2305
Feature extraction, Streaming media, Quality assessment,
Video recording, Training, Solid modeling,
recurrent neural network
BibRef
Chen, P.F.[Peng-Fei],
Li, L.[Leida],
Li, H.L.[Hao-Liang],
Wu, J.J.[Jin-Jian],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
Dynamic Expert-Knowledge Ensemble for Generalizable Video Quality
Assessment,
CirSysVideo(33), No. 6, June 2023, pp. 2577-2589.
IEEE DOI
2306
Quality assessment, Training, Streaming media, Video recording,
Feature extraction, Distortion, Data models, ensemble learning
BibRef
Lin, L.Q.[Li-Qun],
Zheng, Y.[Yang],
Chen, W.L.[Wei-Ling],
Lan, C.D.[Cheng-Dong],
Zhao, T.S.[Tie-Song],
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed
Video Quality Assessment,
SPLetters(30), 2023, pp. 693-697.
IEEE DOI
2307
Visualization, Quality assessment, Video recording,
Predictive models, Feature extraction, Image edge detection,
compression artifact
BibRef
Cao, Y.Q.[Yu-Qin],
Min, X.K.[Xiong-Kuo],
Sun, W.[Wei],
Zhai, G.T.[Guang-Tao],
Subjective and Objective Audio-Visual Quality Assessment for User
Generated Content,
IP(32), 2023, pp. 3847-3861.
IEEE DOI
2307
Databases, Quality assessment, Benchmark testing, Visualization,
Visual databases, Streaming media, Feature extraction, multimodal fusion
BibRef
Cao, Y.Q.[Yu-Qin],
Min, X.K.[Xiong-Kuo],
Sun, W.[Wei],
Zhang, X.P.[Xiao-Ping],
Zhai, G.T.[Guang-Tao],
Audio-Visual Quality Assessment for User Generated Content: Database
and Method,
ICIP23(1495-1499)
IEEE DOI
2312
BibRef
Zhao, K.[Kai],
Yuan, K.[Kun],
Sun, M.[Ming],
Wen, X.[Xing],
Zoom-VQA: Patches, Frames and Clips Integration for Video Quality
Assessment,
NTIRE23(1302-1310)
IEEE DOI
2309
BibRef
Zhang, Z.C.[Zi-Cheng],
Wu, W.[Wei],
Sun, W.[Wei],
Tu, D.Y.[Dan-Yang],
Lu, W.[Wei],
Min, X.K.[Xiong-Kuo],
Chen, Y.[Ying],
Zhai, G.T.[Guang-Tao],
MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videos,
CVPR23(1746-1755)
IEEE DOI
2309
BibRef
Madhusudana, P.C.[Pavan C.],
Birkbeck, N.[Neil],
Wang, Y.L.[Yi-Lin],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
CONVIQT: Contrastive Video Quality Estimator,
IP(32), 2023, pp. 5138-5152.
IEEE DOI
2310
BibRef
Wu, H.N.[Hao-Ning],
Chen, C.F.[Chao-Feng],
Liao, L.[Liang],
Hou, J.W.[Jing-Wen],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Lin, W.S.[Wei-Si],
DisCoVQA: Temporal Distortion-Content Transformers for Video Quality
Assessment,
CirSysVideo(33), No. 9, September 2023, pp. 4840-4854.
IEEE DOI Code:
WWW Link.
2310
BibRef
Wu, H.N.[Hao-Ning],
Chen, C.F.[Chao-Feng],
Liao, L.[Liang],
Hou, J.W.[Jing-Wen],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Gu, J.W.[Jin-Wei],
Lin, W.S.[Wei-Si],
Neighbourhood Representative Sampling for Efficient End-to-End Video
Quality Assessment,
PAMI(45), No. 12, December 2023, pp. 15185-15202.
IEEE DOI
2311
BibRef
Wu, H.N.[Hao-Ning],
Chen, C.F.[Chao-Feng],
Hou, J.W.[Jing-Wen],
Liao, L.[Liang],
Wang, A.[Annan],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Lin, W.S.[Wei-Si],
FAST-VQA: Efficient End-to-End Video Quality Assessment with Fragment
Sampling,
ECCV22(VI:538-554).
Springer DOI
2211
BibRef
Guan, X.D.[Xiao-Di],
Li, F.[Fan],
Zhang, Y.F.[Yang-Fan],
Cosman, P.C.[Pamela C],
End-to-End Blind Video Quality Assessment Based on Visual and Memory
Attention Modeling,
MultMed(25), 2023, pp. 5206-5221.
IEEE DOI
2311
BibRef
Zhou, F.[Fei],
Yuan, S.H.[Shu-Hong],
Liang, Z.J.[Zhi-Jie],
Duan, J.[Jiang],
Qiu, G.P.[Guo-Ping],
A Dataset and Model for the Visual Quality Assessment of Inversely
Tone-Mapped HDR Videos,
IP(33), 2024, pp. 366-381.
IEEE DOI
2401
BibRef
Venkataramanan, A.K.[Abhinau K.],
Stejerean, C.[Cosmin],
Katsavounidis, I.[Ioannis],
Bovik, A.C.[Alan C.],
One Transform to Compute Them All: Efficient Fusion-Based
Full-Reference Video Quality Assessment,
IP(33), 2024, pp. 509-524.
IEEE DOI
2401
Computational modeling, Streaming media, Quality assessment,
Image coding, Solid modeling, Bit rate, Video recording,
contrast sensitivity
BibRef
Zheng, Q.[Qi],
Tu, Z.Z.[Zheng-Zhong],
Madhusudana, P.C.[Pavan C.],
Zeng, X.Y.[Xiao-Yang],
Bovik, A.C.[Alan C.],
Fan, Y.[Yibo],
FAVER: Blind quality prediction of variable frame rate videos,
SP:IC(122), 2024, pp. 117101.
Elsevier DOI Code:
WWW Link.
2402
Video quality assessment, High frame rate, No reference/blind,
Temporal band-pass filter, Natural scene statistics,
Generalized Gaussian distribution
BibRef
Ebenezer, J.P.[Joshua P.],
Shang, Z.[Zaixi],
Wu, Y.J.[Yong-Jun],
Wei, H.[Hai],
Sethuraman, S.[Sriram],
Bovik, A.C.[Alan C.],
HDR-ChipQA: No-reference quality assessment on High Dynamic Range
videos,
SP:IC(129), 2024, pp. 117191.
Elsevier DOI
2411
High dynamic range, Video quality assessment, HDR-ChipQA
BibRef
Saini, S.[Shreshth],
Saha, A.[Avinab],
Bovik, A.C.[Alan C.],
HIDRO-VQA: High Dynamic Range Oracle for Video Quality Assessment,
VAQuality24(469-479)
IEEE DOI Code:
WWW Link.
2404
Databases, Heuristic algorithms, Source coding, Neural networks,
Feature extraction, Quality assessment, High dynamic range
BibRef
Venkataramanan, A.K.[Abhinau K.],
Bovik, A.C.[Alan C.],
Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic
Range Videos,
IP(33), 2024, pp. 5440-5455.
IEEE DOI Code:
HTML Version.
2410
Videos, Databases, Visualization, Standards, Distortion, Brightness,
Quality assessment, High dynamic range, tone mapping, video quality
BibRef
Shang, Z.[Zaixi],
Ebenezer, J.P.[Joshua P.],
Bovik, A.C.[Alan C.],
Wu, Y.J.[Yong-Jun],
Wei, H.[Hai],
Sethuraman, S.[Sriram],
Subjective Assessment Of High Dynamic Range Videos Under Different
Ambient Conditions,
ICIP22(786-790)
IEEE DOI
2211
Databases, Video sequences, Lighting, Transfer functions, Color,
Dynamic range, Quality assessment, High dynamic range (HDR),
ambient illumination
BibRef
Mozhaeva, A.[Anastasia],
Mazin, V.[Vladimir],
Cree, M.J.[Michael J.],
Streeter, L.[Lee],
NRspttemVQA: Real-Time Video Quality Assessment Based on the User's
Visual Perception,
IVCNZ23(1-7)
IEEE DOI
2403
Measurement, Streaming media, Video compression,
Stability analysis, Real-time systems, Quality assessment, visual perception
BibRef
Li, B.Z.[Bin-Zhe],
Chen, B.[Bolin],
Wang, Z.[Zhao],
Chen, B.L.[Bao-Liang],
Wang, S.Q.[Shi-Qi],
Ye, Y.[Yan],
Quality Harmonization for Virtual Composition in Online Video
Communications,
CirSysVideo(34), No. 5, May 2024, pp. 4084-4094.
IEEE DOI
2405
Image coding, Distortion, Image quality, Quality assessment,
Quantization (signal), Image color analysis, Training, quality assessment
BibRef
Ebenezer, J.P.[Joshua P.],
Shang, Z.[Zaixi],
Chen, Y.X.[Yi-Xu],
Wu, Y.J.[Yong-Jun],
Wei, H.[Hai],
Sethuraman, S.[Sriram],
Bovik, A.C.[Alan C.],
HDR or SDR? A Subjective and Objective Study of Scaled and Compressed
Videos,
IP(33), 2024, pp. 3606-3619.
IEEE DOI
2406
Videos, Brightness, TV, Image coding, Solid modeling,
Quality assessment, Measurement, High dynamic range, video compression
BibRef
Zhang, A.X.[Ao-Xiang],
Wang, Y.G.[Yuan-Gen],
Tang, W.X.[Wei-Xuan],
Li, L.[Leida],
Kwong, S.[Sam],
A Spatial-Temporal Video Quality Assessment Method via Comprehensive
HVS Simulation,
Cyber(54), No. 8, August 2024, pp. 4749-4762.
IEEE DOI Code:
WWW Link.
2408
BibRef
Yu, L.[Li],
Wu, S.Y.[Shi-Yu],
Gabbouj, M.[Moncef],
Multi-Swin Transformer Based Spatio-Temporal Information Exploration
for Compressed Video Quality Enhancement,
SPLetters(31), 2024, pp. 1880-1884.
IEEE DOI
2408
Transformers, Convolution, Video recording, Quality assessment,
Motion compensation, Feature extraction, Correlation, swin transformer
BibRef
Chen, L.H.[Li-Heng],
Bampis, C.G.[Christos G.],
Li, Z.[Zhi],
Sole, J.[Joel],
Chen, C.[Chao],
Bovik, A.C.[Alan C.],
Learned fractional downsampling network for adaptive video streaming,
SP:IC(128), 2024, pp. 117172.
Elsevier DOI
2409
Downsampling, Convolutional neural networks,
Adaptive video streaming, Perceptual video quality
BibRef
Sun, W.[Wei],
Wen, W.[Wen],
Min, X.K.[Xiong-Kuo],
Lan, L.[Long],
Zhai, G.T.[Guang-Tao],
Ma, K.[Kede],
Analysis of Video Quality Datasets via Design of Minimalistic Video
Quality Models,
PAMI(46), No. 11, November 2024, pp. 7056-7071.
IEEE DOI
2410
Streaming media, Computational modeling, Distortion, Video recording,
Quality assessment, Visualization, Crowdsourcing, video processing
BibRef
Wen, W.[Wen],
Li, M.[Mu],
Yao, Y.[Yiru],
Sui, X.J.[Xiang-Jie],
Zhang, Y.[Yabin],
Lan, L.[Long],
Fang, Y.M.[Yu-Ming],
Ma, K.[Kede],
Perceptual Quality Assessment of Virtual Reality Videos in the Wild,
CirSysVideo(34), No. 9, September 2024, pp. 8368-8381.
IEEE DOI Code:
WWW Link.
2410
Databases, Distortion, Quality assessment, Streaming media,
Video recording, Spatial resolution, psychophysics
BibRef
Li, X.[Xin],
Yuan, K.[Kun],
Pei, Y.J.[Ya-Jing],
Lu, Y.T.[Yi-Ting],
Sun, M.[Ming],
Zhou, C.[Chao],
Chen, Z.B.[Zhi-Bo],
Timofte, R.[Radu],
Sun, W.[Wei],
Wu, H.N.[Hao-Ning],
Zhang, Z.C.[Zi-Cheng],
Jia, J.[Jun],
Zhang, Z.C.[Zhi-Chao],
Cao, L.[Linhan],
Chen, Q.[Qiubo],
Min, X.K.[Xiong-Kuo],
Lin, W.S.[Wei-Si],
Zhai, G.T.[Guang-Tao],
Sun, J.[JianHui],
Wang, T.Y.[Tian-Yi],
Li, L.[Lei],
Kong, H.[Han],
Wang, W.X.[Wen-Xuan],
Li, B.[Bing],
Luo, C.[Cheng],
Wang, H.Q.[Hai-Qiang],
Chen, X.G.[Xiang-Guang],
Meng, W.H.[Wen-Hui],
Pan, X.[Xiang],
Shi, H.Y.[Hui-Ying],
Zhu, H.[Han],
Xu, X.Z.[Xiao-Zhong],
Sun, L.[Lei],
Chen, Z.Z.[Zhen-Zhong],
Liu, S.[Shan],
Kong, F.Y.[Fang-Yuan],
Fan, H.T.[Hao-Tian],
Xu, Y.F.[Yi-Fang],
Xu, H.R.[Hao-Ran],
Yang, M.[Mengduo],
Zhou, J.[Jie],
Li, J.[Jiaze],
Wen, S.J.[Shi-Jie],
Xu, M.[Mai],
Li, D.[Da],
Yao, S.[Shunyu],
Du, J.Z.[Jia-Zhi],
Zuo, W.M.[Wang-Meng],
Li, Z.B.[Zhi-Bo],
He, S.[Shuai],
Ming, A.[Anlong],
Fu, H.Y.[Hui-Yuan],
Ma, H.D.[Hua-Dong],
Wu, Y.[Yong],
Xue, F.[Fie],
Zhao, G.Z.[Guo-Zhi],
Du, L.[Lina],
Guo, J.[Jie],
Zhang, Y.[Yu],
Zheng, H.M.[Hui-Min],
Chen, J.H.[Jun-Hao],
Liu, Y.[Yue],
Zhou, D.[Dulan],
Xu, K.[Kele],
Xu, Q.[Qisheng],
Sun, T.[Tao],
Ding, Z.X.[Zhi-Xiang],
Hu, Y.H.[Yu-Hang],
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment:
Methods and Results,
NTIRE24(6415-6431)
IEEE DOI Code:
WWW Link.
2410
Training, Reviews, Databases, Benchmark testing, Quality assessment
BibRef
Liu, W.[Wang],
Gao, W.[Wei],
Li, G.[Ge],
Ma, S.W.[Si-Wei],
Zhao, T.S.[Tie-Song],
Yuan, H.[Hui],
Enlarged Motion-Aware and Frequency-Aware Network for Compressed
Video Artifact Reduction,
CirSysVideo(34), No. 10, October 2024, pp. 10339-10352.
IEEE DOI
2411
Convolution, Feature extraction, Task analysis, Video compression,
Quantization (signal), Video recording,
video quality enhancement
BibRef
Zheng, R.[Ruidi],
Jiang, X.[Xiuhua],
SR4KVQA: Video quality assessment database and metric for 4K
super-resolution,
JVCIR(104), 2024, pp. 104290.
Elsevier DOI Code:
WWW Link.
2411
Super-resolution (SR), 4K video quality assessment database,
Blind video quality assessment (BVQA)
BibRef
Zhang, Q.[Qi],
Wang, S.S.[Shan-She],
Zhang, X.F.[Xin-Feng],
Jia, C.M.[Chuan-Min],
Wang, Z.[Zhao],
Ma, S.W.[Si-Wei],
Gao, W.[Wen],
Perceptual Video Coding for Machines via Satisfied Machine Ratio
Modeling,
PAMI(46), No. 12, December 2024, pp. 7651-7668.
IEEE DOI
2411
Image coding, Task analysis, Visualization, Codecs, Encoding,
Video coding, Optimization, Video coding for machines,
satisfied user ratio
BibRef
Yang, J.[Jifan],
Wang, Z.Y.[Zhong-Yuan],
Huang, B.[Baojin],
Ai, J.X.[Jia-Xin],
Yang, Y.H.[Yu-Hong],
Xiao, J.[Jing],
Xiong, Z.X.[Zi-Xiang],
Luminance decomposition and reconstruction for high dynamic range
Video Quality Assessment,
PR(158), 2025, pp. 111011.
Elsevier DOI
2411
High dynamic range, Video quality assessment,
Luminance decomposition, Feature reorganisation
BibRef
Wang, Y.L.[Yi-Lin],
Yim, J.G.[Joong Gon],
Birkbeck, N.[Neil],
Adsumilli, B.[Balu],
Youtube SFV+HDR Quality Dataset,
ICIP24(96-102)
IEEE DOI
2411
Video on demand, Image color analysis, User-generated content,
Focusing, Quality assessment, High dynamic range, Web sites,
Crowd-sourcing subjective test
BibRef
Yan, J.[Jiebin],
Wu, L.[Lei],
Fang, Y.M.[Yu-Ming],
Liu, X.[Xuelin],
Xia, X.[Xue],
Liu, W.[Weide],
Video Quality Assessment for Online Processing: From Spatial to
Temporal Sampling,
CirSysVideo(34), No. 12, December 2024, pp. 13441-13451.
IEEE DOI
2501
Feature extraction, Quality assessment, Video recording,
Computational modeling, Distortion, Visualization,
video understanding
BibRef
Zuo, W.M.[Wang-Meng],
Zhao, D.B.[De-Bin],
Enhancing No-Reference Audio-Visual Quality Assessment via Joint
Cross-Attention Fusion,
SPLetters(32), 2025, pp. 556-560.
IEEE DOI
2501
Feature extraction, Visualization, Quality assessment,
Transformers, Correlation, Computational modeling, transformer
BibRef
Wan, Z.L.[Zhao-Lin],
Hao, X.[Xiguang],
Fan, X.P.[Xiao-Peng],
Zuo, W.M.[Wang-Meng],
Zhao, D.B.[De-Bin],
Enhancing No-Reference Audio-Visual Quality Assessment via Joint
Cross-Attention Fusion,
SPLetters(32), 2025, pp. 556-560.
IEEE DOI
2501
Feature extraction, Visualization, Quality assessment,
Transformers, Correlation, Computational modeling
BibRef
Wen, W.[Wen],
Li, M.[Mu],
Zhang, Y.[Yabin],
Liao, Y.T.[Yi-Ting],
Li, J.L.[Jun-Lin],
Zhang, L.[Li],
Ma, K.[Kede],
Modular Blind Video Quality Assessment,
CVPR24(2763-2772)
IEEE DOI
2410
Training, Analytical models, Visualization, Computational modeling,
User-generated content, Rectifiers, Predictive models
BibRef
Zhu, Q.[Qiang],
Hao, J.H.[Jin-Hua],
Ding, Y.[Yukang],
Liu, Y.[Yu],
Mo, Q.[Qiao],
Sun, M.[Ming],
Zhou, C.[Chao],
Zhu, S.Y.[Shu-Yuan],
CPGA: Coding Priors-Guided Aggregation Network for Compressed Video
Quality Enhancement,
CVPR24(2964-2974)
IEEE DOI Code:
WWW Link.
2410
Video coding, Correlation, Aggregates, Computational modeling,
Encoding, Vectors, video quality enhancement, video compression,
coding priors
BibRef
Lu, Y.T.[Yi-Ting],
Li, X.[Xin],
Pei, Y.J.[Ya-Jing],
Yuan, K.[Kun],
Xie, Q.Z.[Qi-Zhi],
Qu, Y.P.[Yun-Peng],
Sun, M.[Ming],
Zhou, C.[Chao],
Chen, Z.B.[Zhi-Bo],
KVQ: Kwai Video Quality Assessment for Short-form Videos,
CVPR24(25963-25973)
IEEE DOI Code:
WWW Link.
2410
Video on demand, Databases, Semantics, Transcoding, Media, Distortion,
Quality assessment, quality assessment, short-form video, UGC, Dataset
BibRef
He, C.L.[Chen-Long],
Zheng, Q.[Qi],
Zhu, R.X.[Ruo-Xi],
Zeng, X.Y.[Xiao-Yang],
Fan, Y.[Yibo],
Tu, Z.Z.[Zheng-Zhong],
COVER: A Comprehensive Video Quality Evaluator,
AIS24(5799-5809)
IEEE DOI Code:
WWW Link.
2410
Visualization, Semantics, User-generated content, Streaming media,
Feature extraction, Transformers, Video Quality Assessment,
User-generated Content
BibRef
Xu, H.R.[Hao-Ran],
Yang, M.[Mengduo],
Zhou, J.[Jie],
Li, J.[Jiaze],
Short-form UGC Video Quality Assessment Based on Multi-Level Video
Fusion with Rank-Aware,
NTIRE24(6297-6306)
IEEE DOI
2410
Adaptation models, Video on demand, Manuals, Propulsion,
Data augmentation, Data models, Quality assessment
BibRef
Lu, Y.T.[Yi-Ting],
Li, X.[Xin],
Li, B.C.[Bing-Chen],
Yu, Z.[Zihao],
Guan, F.[Fengbin],
Wang, X.R.[Xin-Rui],
Liao, R.[Ruling],
Ye, Y.[Yan],
Chen, Z.B.[Zhi-Bo],
AIGC-VQA: A Holistic Perception Metric for AIGC Video Quality
Assessment,
NTIRE24(6384-6394)
IEEE DOI
2410
Measurement, Training, Adaptation models, Diffusion models,
Explosives, Quality assessment, AIGC, Video Quality Assessment
BibRef
Qu, B.[Bowen],
Liang, X.Y.[Xiao-Yu],
Sun, S.[Shangkun],
Gao, W.[Wei],
Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text
Consistency and Domain Distribution Gap,
NTIRE24(6652-6660)
IEEE DOI
2410
Visualization, Computational modeling, Predictive models,
Quality assessment
BibRef
Huang, D.J.[Ding-Jiun],
Kao, Y.T.[Yu-Ting],
Chuang, T.H.[Tieh-Hung],
Tsai, Y.C.[Ya-Chun],
Lou, J.K.[Jing-Kai],
Guan, S.H.[Shuen-Huei],
SB-VQA: A Stack-Based Video Quality Assessment Framework for Video
Enhancement,
NTIRE23(1613-1622)
IEEE DOI
2309
BibRef
Wu, H.N.[Hao-Ning],
Zhang, E.[Erli],
Liao, L.[Liang],
Chen, C.F.[Chao-Feng],
Hou, J.W.[Jing-Wen],
Wang, A.[Annan],
Sun, W.X.[Wen-Xiu],
Yan, Q.[Qiong],
Lin, W.S.[Wei-Si],
Exploring Video Quality Assessment on User Generated Contents from
Aesthetic and Technical Perspectives,
ICCV23(20087-20097)
IEEE DOI Code:
WWW Link.
2401
BibRef
Yang, Y.[Yang],
Jiang, B.[Bo],
Wu, K.L.[Kai-Lin],
Prnet: A Progressive Regression Network for No-Reference
User-Generated-Content (UGC) Video Quality Assessment,
ICIP23(640-644)
IEEE DOI
2312
BibRef
Zhang, Z.C.[Zi-Cheng],
Zhou, Y.J.[Ying-Jie],
Sun, W.[Wei],
Min, X.K.[Xiong-Kuo],
Zhai, G.T.[Guang-Tao],
Geometry-Aware Video Quality Assessment for Dynamic Digital Human,
ICIP23(1365-1369)
IEEE DOI
2312
BibRef
Pasquarella, V.J.[Valerie J.],
Brown, C.F.[Christopher F.],
Czerwinski, W.[Wanda],
Rucklidge, W.J.[William J.],
Comprehensive quality assessment of optical satellite imagery using
weakly supervised video learning,
EarthVision23(2125-2135)
IEEE DOI
2309
BibRef
Agarla, M.[Mirko],
Celona, L.[Luigi],
Rota, C.[Claudio],
Schettini, R.[Raimondo],
Quality assessment of enhanced videos guided by aesthetics and
technical quality attributes,
NTIRE23(1533-1541)
IEEE DOI
2309
BibRef
Li, Z.[Zutong],
Yang, L.[Lei],
DCVQE: A Hierarchical Transformer for Video Quality Assessment,
ACCV22(IV:398-416).
Springer DOI
2307
BibRef
Fontanel, D.[Dario],
Higham, D.[David],
Vallade, B.Q.A.[Benoit Quentin Arthur],
On the Importance of Spatio-Temporal Learning for Video Quality
Assessment,
VAQuality23(1-7)
IEEE DOI
2302
Correlation, Conferences, User-generated content,
Quality assessment, Reliability, Video recording
BibRef
Han, X.H.[Xiao-Hao],
Zhang, W.[Wei],
Pu, J.[Jian],
Compressed Video Quality Enhancement with Motion Approximation and
Blended Attention,
ICPR22(338-344)
IEEE DOI
2212
Deep learning, Fluctuations, Neural networks, Feature extraction,
Robustness, Quality assessment
BibRef
Han, X.H.[Xiao-Hao],
Zhang, W.[Wei],
Pu, J.[Jian],
Exploring Spatiotemporal Relationships for Improving Compressed Video
Quality,
ICPR22(400-406)
IEEE DOI
2212
Interpolation, Benchmark testing, Spatiotemporal phenomena,
Quality assessment, Calibration, Data mining, Video recording
BibRef
Perrin, A.F.[Anne-Flore],
Dormeval, C.[Charles],
Wang, Y.L.[Yi-Lin],
Birkbeck, N.[Neil],
Adsumilli, B.[Balu],
Le Callet, P.[Patrick],
When is the Cleaning of Subjective Data Relevant to Train UGC Video
Quality Metrics?,
ICIP22(1466-1470)
IEEE DOI
2211
Visualization, Uncertainty, Biological system modeling,
Benchmark testing, Cleaning, Data models, Quality assessment, Training metrics
BibRef
Wang, Y.L.[Yi-Lin],
Yim, J.G.[Joong Gon],
Birkbeck, N.[Neil],
Ke, J.J.[Jun-Jie],
Talebi, H.[Hossein],
Chen, X.[Xi],
Yang, F.[Feng],
Adsumilli, B.[Balu],
Revisiting the Efficiency of UGC Video Quality Assessment,
ICIP22(3016-3020)
IEEE DOI
2211
Training, Image coding, Data collection, Distortion,
Feature extraction, Data models, Quality assessment,
Efficient Network
BibRef
Xing, F.C.[Feng-Chuang],
Wang, Y.G.[Yuan-Gen],
Wang, H.[Hanpin],
Li, L.[Leida],
Zhu, G.P.[Guo-Pu],
Starvqa: Space-Time Attention for Video Quality Assessment,
ICIP22(2326-2330)
IEEE DOI
2211
Training, Image coding, Video sequences, Transformers, Distortion,
video quality assessment, in-the-wild videos,
Transformer
BibRef
Beghdadi, A.[Azeddine],
Qureshi, M.A.[Muhammad Ali],
Dakkar, B.E.[Borhen-Eddine],
Gillani, H.H.[Hammad Hassan],
Khan, Z.A.[Zohaib Amjad],
Kaaniche, M.[Mounir],
Ullah, M.[Mohib],
Cheikh, F.A.[Faouzi Alaya],
A New Video Quality Assessment Dataset for Video Surveillance
Applications,
ICIP22(1521-1525)
IEEE DOI
2211
Night vision, Databases, Benchmark testing, Distortion,
Video surveillance, Quality assessment, Video Surveillance,
Distortion generation
BibRef
Wu, X.B.[Xin-Bo],
Dong, Z.Y.[Zheng-Yan],
Zhang, F.[Fan],
Rosin, P.L.[Paul L.],
Liu, H.T.[Han-Tao],
Analysis of Video Quality Induced Spatio-Temporal Saliency Shifts,
ICIP22(1581-1585)
IEEE DOI
2211
Video coding, Visualization, Systematics, Databases,
Statistical analysis, Gaze tracking, Distortion, Video quality, gaze,
eye-tracking
BibRef
You, J.Y.[Jun-Yong],
Lin, Y.[Yuan],
Efficient Transformer with Locally Shared Attention for Video Quality
Assessment,
ICIP22(356-360)
IEEE DOI
2211
Image quality, Databases, Video sequences, Memory management,
Transformers, Quality assessment, Attention, Transformer,
video quality assessment (VQA)
BibRef
Pastor, A.[Andréas],
Krasula, L.[Lukáš],
Zhu, X.Q.[Xiao-Qing],
Li, Z.[Zhi],
Le Callet, P.[Patrick],
On the Accuracy of Open Video Quality Metrics for Local Decision in
AV1 Video Codec,
ICIP22(4013-4017)
IEEE DOI
2211
Measurement, Maximum likelihood estimation, Image coding,
Quality assessment, Electron tubes, Video codecs, Video recording,
Open Video Codecs
BibRef
Çetinkaya, E.[Ekrem],
Nguyen, M.[Minh],
Timmerer, C.[Christian],
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement
with Deep Neural Networks,
MMMod22(II:465-472).
Springer DOI
2203
BibRef
Tu, Z.Z.[Zheng-Zhong],
Chen, C.J.[Chia-Ju],
Wang, Y.L.[Yi-Lin],
Birkbeck, N.[Neil],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
Video Quality Assessment of User Generated Content:
A Benchmark Study and a New Model,
ICIP21(1409-1413)
IEEE DOI
2201
Visualization, Systematics, Computational modeling,
User-generated content, Transfer learning, Benchmark testing,
no-reference
BibRef
Zhang, Z.C.[Zi-Cheng],
Lu, W.[Wei],
Sun, W.[Wei],
Min, X.K.[Xiong-Kuo],
Wang, T.[Tao],
Zhai, G.T.[Guang-Tao],
Surveillance Video Quality Assessment Based on Quality Related
Retraining,
ICIP22(4278-4282)
IEEE DOI
2211
Head, Databases, Surveillance, Distortion, Multitasking,
Video surveillance, Quality assessment, Surveillance videos,
video quality assessment
BibRef
Yi, F.[Fuwang],
Chen, M.[Mianyi],
Sun, W.[Wei],
Min, X.K.[Xiong-Kuo],
Tian, Y.[Yuan],
Zhai, G.T.[Guang-Tao],
Attention Based Network for No-Reference UGC Video Quality Assessment,
ICIP21(1414-1418)
IEEE DOI
2201
Databases, User-generated content, Neural networks, Visual systems,
Logic gates, Feature extraction, Distortion,
attention mechanism
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Tu, Z.Z.[Zheng-Zhong],
Chen, C.J.[Chia-Ju],
Wang, Y.L.[Yi-Lin],
Birkbeck, N.[Neil],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
A Temporal Statistics Model for UGC Video Quality Prediction,
ICIP21(1454-1458)
IEEE DOI
2201
Analytical models, Databases, Computational modeling,
Image processing, User-generated content, Predictive models,
user-generated content
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Bhat, M.[Madhukar],
Thiesse, J.M.[Jean-Marc],
Le Callet, P.[Patrick],
Combining Video Quality Metrics To Select Perceptually Accurate
Resolution In A Wide Quality Range: A Case Study,
ICIP21(2164-2168)
IEEE DOI
2201
Measurement, Radio frequency, Image resolution, Image coding,
Diversity reception, Encoding, The adaptive resolution,
perceptual performance
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Ying, Z.Q.[Zhen-Qiang],
Mandal, M.[Maniratnam],
Ghadiyaram, D.[Deepti],
Bovik, A.C.[Alan C.],
Patch-VQ: 'Patching Up' the Video Quality Problem,
CVPR21(14014-14024)
IEEE DOI
2111
User-generated content, Streaming media, Predictive models,
Distortion, Data models, Quality assessment
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Chen, H.M.[Hua-Mei],
Chen, G.S.[Gen-She],
Blasch, E.[Erik],
On the Development of a Classification Based Automated Motion Imagery
Interpretability Prediction,
WAAMI20(75-88).
Springer DOI
2103
Video National Imagery Interpretability Rating Scale -- human analyst based.
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Tang, J.,
Dong, Y.,
Xie, R.,
Gu, X.,
Song, L.,
Li, L.,
Zhou, B.,
Deep Blind Video Quality Assessment for User Generated Videos,
VCIP20(156-159)
IEEE DOI
2102
Feature extraction, Quality assessment, Video recording,
Streaming media, Databases, Adaptation models, Kernel, no reference
BibRef
Zhou, W.,
Chen, Z.,
Deep Local and Global Spatiotemporal Feature Aggregation for Blind
Video Quality Assessment,
VCIP20(338-341)
IEEE DOI
2102
Quality assessment, Video recording, Feature extraction,
Spatiotemporal phenomena, Databases, Indexes, Deep learning,
spatiotemporal aggregation
BibRef
Wu, W.[Wei],
Liu, Z.Z.[Zi-Zheng],
Chen, Z.Z.[Zhen-Zhong],
Liu, S.[Shan],
No-Reference Video Quality Assessment Based On Similarity Map
Estimation,
ICIP20(181-185)
IEEE DOI
2011
Quality assessment, Feature extraction, Video recording,
Databases, Image analysis,
spatio-temporal pooling
BibRef
Wang, X.,
Wang, K.,
Yang, B.,
Li, F.W.B.,
Liang, X.,
Perceptual Quality Assessment On DIBR Synthesized Videos With
Composite Distortions,
ICIP20(186-190)
IEEE DOI
2011
Videos, Distortion, Databases, Quality assessment,
Measurement, video quality assessment,
objective study
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Yim, J.G.,
Wang, Y.,
Birkbeck, N.,
Adsumilli, B.,
Subjective Quality Assessment for Youtube UGC Dataset,
ICIP20(131-135)
IEEE DOI
2011
Quality assessment, YouTube, Correlation, Video recording,
Video compression, Standards, Video quality assessment,
Crowd-sourcing
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Li, C.[Chen],
Xu, M.[Mai],
Jiang, L.[Lai],
Zhang, S.[Shanyi],
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Viewport Proposal CNN for 360deg Video Quality Assessment,
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IEEE DOI
2002
BibRef
Wang, Q.,
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A Fidelity-Assured Rate Distortion Optimization Method for
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ICIP19(4135-4139)
IEEE DOI
1910
fidelity, perceptual quality, structural similarity (SSIM) index,
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BibRef
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A No-Reference Autoencoder Video Quality Metric,
ICIP19(1755-1759)
IEEE DOI
1910
no-reference quality metric, autoencoder, video quality,
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BibRef
Tamboli, R.R.,
Kara, P.A.,
Cserkaszky, A.,
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Martini, M.G.,
Appina, B.,
Channappayya, S.S.,
Jana, S.,
3D Objective Quality Assessment of Light Field Video Frames,
3DTV-CON18(1-4)
IEEE DOI
1812
cameras, video signal processing,
light field displays, light field content creation,
objective metric
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Zhang, F.,
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BVI-HD: A Video Quality Database for HEVC Compressed and Texture
Synthesized Content,
MultMed(20), No. 10, October 2018, pp. 2620-2630.
IEEE DOI
1810
data compression, high definition video, image sequences,
video coding, video signal processing, HEVC compression,
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Danier, D.[Duolikun],
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BibRef
Nasiri, R.M.,
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Temporal Motion Smoothness and the Impact of Frame Rate Variation on
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ICIP18(1418-1422)
IEEE DOI
1809
Motion measurement, Video recording, Quality assessment,
Histograms, Correlation, Wavelet transforms, Quality of experience,
complex wavelet transform
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Dinh, K.Q.,
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Kim, J.,
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ICIP18(2496-2500)
IEEE DOI
1809
Measurement, Encoding, Quality assessment, Video coding,
Quantization (signal), Training, Kernel, Video quality assessment,
convolutional neural network
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Yang, S.[Shu],
Zhao, J.Z.[Jun-Zhe],
Jiang, T.T.[Ting-Ting],
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VCIP17(1-4)
IEEE DOI
1804
quality of experience, video signal processing, virtual reality,
Virtual Reality technology,
video quality assessment
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Zhu, Y.[Yun],
Wang, Y.F.[Yong-Fang],
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Blind video quality assessment based on spatio-temporal internal
generative mechanism,
ICIP17(305-309)
IEEE DOI
1803
Correlation, Distortion, Predictive models, Quality assessment,
Streaming media, Video recording, Visualization,
video quality assessment
BibRef
Chaabouni, A.,
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Quality assessment of MPEG-4 AVC/H.264 and HEVC compressed video in a
telemedicine context,
ICIP17(3465-3469)
IEEE DOI
1803
Encoding, Measurement, Medical diagnostic imaging, Observers,
Quality assessment, Standards,
biomedical image processing
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Ghadiyaram, D.,
Chen, C.,
Inguva, S.,
Kokaram, A.,
A no-reference video quality predictor for compression and scaling
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ICIP17(3445-3449)
IEEE DOI
1803
Databases, Distortion, Feature extraction, Quality assessment,
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An Exploratory Comparison of the Visual Quality of Virtual Reality
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1712
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Duan, H.,
Zhai, G.,
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Zhu, W.,
IVQAD 2017: An immersive video quality assessment database,
WSSIP17(1-5)
IEEE DOI
1707
Bit rate, Cameras, Databases, Quality assessment, Video recording,
Virtual reality, Visual systems, Immersive video, database,
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Liu, D.W.[Dong-Wei],
Klette, R.,
Sharpness and contrast measures on videos,
ICVNZ15(1-6)
IEEE DOI
1701
computer graphics
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Mantiuk, R.K.[Rafal K.],
Training a Task-Specific Image Reconstruction Loss,
WACV22(21-30)
IEEE DOI
2202
Training, Image resolution, Semantics, Transform coding, Observers,
Feature extraction, Distortion, Computational Photography,
Image Processing -> Image Restoration
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Mantiuk, R.K.[Rafal K.],
Practicalities of predicting quality of high dynamic range images and
video,
ICIP16(904-908)
IEEE DOI
1610
Brightness
BibRef
Kim, H.G.,
Ro, Y.M.,
Measurement of critical temporal inconsistency for quality assessment
of synthesized video,
ICIP16(1027-1031)
IEEE DOI
1610
Distortion
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Quality assurance in large collections of video sequences,
ICIP15(3580-3584)
IEEE DOI
1512
automatic quality assurance; large video databases; time synchronization
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Wang, M.M.[Meng-Meng],
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A very low complexity reduced reference video quality metric based on
spatio-temporal information selection,
ICIP15(571-575)
IEEE DOI
1512
Video quality assessment
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Studying human behavioural responses to time-varying distortions for
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ICIP15(651-655)
IEEE DOI
1512
Video quality assessment
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Mirkovic, M.[Milan],
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Video Quality Assessment for Mobile Devices on Mobile Devices,
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Springer DOI
1511
BibRef
Xu, M.[Mai],
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A novel objective quality assessment method for perceptual video
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VCIP14(29-32)
IEEE DOI
1504
Gaussian processes
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ICIP14(541-545)
IEEE DOI
1502
Databases
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Assessment of video naturalness using time-frequency statistics,
ICIP14(571-574)
IEEE DOI
1502
Computational modeling
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Delivery quality score model for Internet video,
ICIP14(2007-2011)
IEEE DOI
1502
Delays
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Video image quality analysis for enhancing tracker performance,
AIPR13(1-9)
IEEE DOI
1408
object tracking
BibRef
Cardoso, J.V.M.,
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Oliveira, I.P.,
Temporal analysis and perceptual weighting for objective video
quality measurement,
Southwest14(57-60)
IEEE DOI
1406
IP networks
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1502
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Measurement
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Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Video Quality for Stereo, 3D Video .