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Vlad Hosu
Vlad Hosu
Sony AI
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Titel
Zitiert von
Zitiert von
Jahr
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment
V Hosu, H Lin, T Sziranyi, D Saupe
IEEE Transactions on Image Processing 29, 4041-4056, 2020
520*2020
KADID-10k: A large-scale artificially distorted IQA database
H Lin, V Hosu, D Saupe
2019 Eleventh International Conference on Quality of Multimedia Experience …, 2019
3552019
The Konstanz natural video database (KoNViD-1k)
V Hosu, F Hahn, M Jenadeleh, H Lin, H Men, T Szirányi, S Li, D Saupe
2017 Ninth international conference on quality of multimedia experience …, 2017
2812017
Effective aesthetics prediction with multi-level spatially pooled features
V Hosu, B Goldlucke, D Saupe
proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
1552019
KonVid-150k: A dataset for no-reference video quality assessment of videos in-the-wild
F Götz-Hahn, V Hosu, H Lin, D Saupe
IEEE Access 9, 72139-72160, 2021
56*2021
DeepFL-IQA: Weak supervision for deep IQA feature learning
H Lin, V Hosu, D Saupe
arXiv preprint arXiv:2001.08113, 2020
502020
Crowd workers proven useful: A comparative study of subjective video quality assessment
D Saupe, F Hahn, V Hosu, I Zingman, M Rana, S Li
502016
SUR-Net: Predicting the satisfied user ratio curve for image compression with deep learning
C Fan, H Lin, V Hosu, Y Zhang, Q Jiang, R Hamzaoui, D Saupe
2019 eleventh international conference on quality of multimedia experience …, 2019
252019
SUR-FeatNet: Predicting the satisfied user ratio curve for image compression with deep feature learning
H Lin, V Hosu, C Fan, Y Zhang, Y Mu, R Hamzaoui, D Saupe
Quality and User Experience 5, 1-23, 2020
232020
Large-scale crowdsourced subjective assessment of picturewise just noticeable difference
H Lin, G Chen, M Jenadeleh, V Hosu, UD Reips, R Hamzaoui, D Saupe
IEEE transactions on circuits and systems for video technology 32 (9), 5859-5873, 2022
222022
Koniq++: Boosting no-reference image quality assessment in the wild by jointly predicting image quality and defects
S Su, V Hosu, H Lin, Y Zhang, D Saupe
The 32nd British Machine Vision Conference, 2021
202021
Disregarding the big picture: Towards local image quality assessment
O Wiedemann, V Hosu, H Lin, D Saupe
2018 Tenth international conference on quality of multimedia experience …, 2018
202018
Expertise screening in crowdsourcing image quality
V Hosu, H Lin, D Saupe
2018 Tenth international conference on quality of multimedia experience …, 2018
192018
Evolgan: Evolutionary generative adversarial networks
B Roziere, F Teytaud, V Hosu, H Lin, J Rapin, M Zameshina, O Teytaud
Proceedings of the Asian Conference on Computer Vision, 2020
182020
Visual quality assessment for interpolated slow-motion videos based on a novel database
H Men, V Hosu, H Lin, A Bruhn, D Saupe
2020 Twelfth International Conference on Quality of Multimedia Experience …, 2020
112020
Saliency-driven image coding improves overall perceived JPEG quality
V Hosu, F Hahn, O Wiedemann, SH Jung, D Saupe
2016 Picture Coding Symposium (PCS), 1-5, 2016
112016
Tarsier: Evolving noise injection in super-resolution gans
B Roziere, NC Rakotonirina, V Hosu, A Rasoanaivo, H Lin, C Couprie, ...
2020 25th International Conference on Pattern Recognition (ICPR), 7028-7035, 2021
102021
Foveated video coding for real-time streaming applications
O Wiedemann, V Hosu, H Lin, D Saupe
2020 Twelfth International Conference on Quality of Multimedia Experience …, 2020
92020
Visual quality assessment for motion compensated frame interpolation
H Men, H Lin, V Hosu, D Maurer, A Bruhn, D Saupe
2019 Eleventh International Conference on Quality of Multimedia Experience …, 2019
92019
Critical analysis on the reproducibility of visual quality assessment using deep features
F Götz-Hahn, V Hosu, D Saupe
Plos one 17 (8), e0269715, 2022
82022
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