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ORCIDVlad Hosu
Person information
- affiliation: University of Konstanz, Department of Computer and Information Science, Germany
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2020 – today
- 2024
[j8]Shaolin Su
, Hanhe Lin, Vlad Hosu, Oliver Wiedemann, Jinqiu Sun, Yu Zhu, Hantao Liu, Yanning Zhang, Dietmar Saupe:
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model. IEEE Trans. Multim. 26: 2671-2685 (2024)- [i17]Vlad Hosu, Lorenzo Agnolucci, Oliver Wiedemann, Daisuke Iso:
UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality Assessment. CoRR abs/2406.17472 (2024) - [i16]Vlad Hosu, Marcos V. Conde, Lorenzo Agnolucci, Nabajeet Barman, Saman Zadtootaghaj, Radu Timofte:
AIM 2024 Challenge on UHD Blind Photo Quality Assessment. CoRR abs/2409.16271 (2024) - 2023
- [j7]Oliver Wiedemann, Vlad Hosu, Shaolin Su, Dietmar Saupe:
Konx: cross-resolution image quality assessment. Qual. User Exp. 8(1) (2023) - [c18]Michela Testolina, Vlad Hosu, Mohsen Jenadeleh, Davi Lazzarotto, Dietmar Saupe, Touradj Ebrahimi:
JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range. QoMEX 2023: 55-60 - 2022
- [j6]Hanhe Lin, Guangan Chen, Mohsen Jenadeleh, Vlad Hosu, Ulf-Dietrich Reips, Raouf Hamzaoui, Dietmar Saupe:
Large-Scale Crowdsourced Subjective Assessment of Picturewise Just Noticeable Difference. IEEE Trans. Circuits Syst. Video Technol. 32(9): 5859-5873 (2022) - [c17]Mariia Zameshina, Olivier Teytaud, Fabien Teytaud, Vlad Hosu, Nathanaël Carraz Rakotonirina, Laurent Najman, Markus Wagner:
Fairness in generative modeling: do it unsupervised! GECCO Companion 2022: 320-323 - [i15]Shaolin Su, Hanhe Lin, Vlad Hosu, Oliver Wiedemann, Jinqiu Sun, Yu Zhu, Hantao Liu, Yanning Zhang, Dietmar Saupe:
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model. CoRR abs/2207.04904 (2022) - [i14]Mariia Zameshina, Olivier Teytaud, Fabien Teytaud, Vlad Hosu, Nathanaël Carraz, Laurent Najman, Markus Wagner:
Fairness in generative modeling. CoRR abs/2210.03517 (2022) - [i13]Oliver Wiedemann, Vlad Hosu, Shaolin Su, Dietmar Saupe:
KonX: Cross-Resolution Image Quality Assessment. CoRR abs/2212.05813 (2022) - 2021
- [j5]Franz Götz-Hahn, Vlad Hosu, Hanhe Lin, Dietmar Saupe:
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild. IEEE Access 9: 72139-72160 (2021) - [c16]Shaolin Su, Vlad Hosu, Hanhe Lin, Yanning Zhang, Dietmar Saupe:
KonIQ++: Boosting No-Reference Image Quality Assessment in the Wild by Jointly Predicting Image Quality and Defects. BMVC 2021: 330 - 2020
- [j4]Hanhe Lin, Vlad Hosu, Chunling Fan, Yun Zhang, Yuchen Mu, Raouf Hamzaoui, Dietmar Saupe:
SUR-FeatNet: Predicting the satisfied user ratio curve for image compression with deep feature learning. Qual. User Exp. 5(1) (2020) - [j3]Hui Men, Vlad Hosu, Hanhe Lin, Andrés Bruhn, Dietmar Saupe:
Subjective annotation for a frame interpolation benchmark using artefact amplification. Qual. User Exp. 5(1) (2020) - [j2]Vlad Hosu, Hanhe Lin, Tamás Szirányi, Dietmar Saupe:
KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment. IEEE Trans. Image Process. 29: 4041-4056 (2020) - [c15]Baptiste Rozière, Fabien Teytaud, Vlad Hosu, Hanhe Lin, Jérémy Rapin, Mariia Zameshina, Olivier Teytaud:
EvolGAN: Evolutionary Generative Adversarial Networks. ACCV (4) 2020: 679-694 - [c14]Baptiste Rozière, Nathanaël Carraz Rakotonirina, Vlad Hosu, Hanhe Lin, Andry Rasoanaivo, Olivier Teytaud, Camille Couprie:
Evolutionary super-resolution. GECCO Companion 2020: 151-152 - [c13]Baptiste Rozière, Nathanaël Carraz Rakotonirina, Vlad Hosu, Andry Rasoanaivo, Hanhe Lin, Camille Couprie, Olivier Teytaud:
Tarsier: Evolving Noise Injection in Super-Resolution GANs. ICPR 2020: 7028-7035 - [c12]Tanaya Guha, Vlad Hosu, Dietmar Saupe, Bastian Goldlücke, Naveen Kumar, Weisi Lin, Victor R. Martinez, Krishna Somandepalli, Shrikanth Narayanan, Wen-Huang Cheng, Kree McLaughlin, Hartwig Adam, John See, Lai-Kuan Wong:
ATQAM/MAST'20: Joint Workshop on Aesthetic and Technical Quality Assessment of Multimedia and Media Analytics for Societal Trends. ACM Multimedia 2020: 4758-4760 - [c11]Hui Men, Vlad Hosu, Hanhe Lin, Andrés Bruhn, Dietmar Saupe:
Visual Quality Assessment for Interpolated Slow-Motion Videos Based on a Novel Database. QoMEX 2020: 1-6 - [c10]Oliver Wiedemann, Vlad Hosu, Hanhe Lin, Dietmar Saupe:
Foveated Video Coding for Real-Time Streaming Applications. QoMEX 2020: 1-6 - [c9]Mai Lan Ha, Vlad Hosu, Volker Blanz:
Color Composition Similarity and Its Application in Fine-grained Similarity. WACV 2020: 2548-2557 - [i12]Hanhe Lin, Vlad Hosu, Chunling Fan, Yun Zhang, Yuchen Mu, Raouf Hamzaoui, Dietmar Saupe:
SUR-FeatNet: Predicting the Satisfied User Ratio Curvefor Image Compression with Deep Feature Learning. CoRR abs/2001.02002 (2020) - [i11]Hui Men, Vlad Hosu, Hanhe Lin, Andrés Bruhn, Dietmar Saupe:
Subjective Annotation for a Frame Interpolation Benchmark using Artifact Amplification. CoRR abs/2001.06409 (2020) - [i10]Hanhe Lin, Vlad Hosu, Dietmar Saupe:
DeepFL-IQA: Weak Supervision for Deep IQA Feature Learning. CoRR abs/2001.08113 (2020) - [i9]Franz Götz-Hahn, Vlad Hosu, Dietmar Saupe:
Comment on "No-Reference Video Quality Assessment Based on the Temporal Pooling of Deep Features". CoRR abs/2005.04400 (2020) - [i8]Franz Götz-Hahn, Vlad Hosu, Dietmar Saupe:
Critical analysis on the reproducibility of visual quality assessment using deep features. CoRR abs/2009.05369 (2020) - [i7]Baptiste Rozière, Nathanaël Carraz Rakotonirina, Vlad Hosu, Andry Rasoanaivo, Hanhe Lin, Camille Couprie, Olivier Teytaud:
Tarsier: Evolving Noise Injection in Super-Resolution GANs. CoRR abs/2009.12177 (2020) - [i6]Baptiste Rozière, Fabien Teytaud, Vlad Hosu, Hanhe Lin, Jérémy Rapin, Mariia Zameshina, Olivier Teytaud:
EvolGAN: Evolutionary Generative Adversarial Networks. CoRR abs/2009.13311 (2020)
2010 – 2019
- 2019
- [c8]Vlad Hosu, Bastian Goldlücke, Dietmar Saupe:
Effective Aesthetics Prediction With Multi-Level Spatially Pooled Features. CVPR 2019: 9375-9383 - [c7]Chunling Fan, Hanhe Lin, Vlad Hosu, Yun Zhang, Qingshan Jiang, Raouf Hamzaoui, Dietmar Saupe:
SUR-Net: Predicting the Satisfied User Ratio Curve for Image Compression with Deep Learning. QoMEX 2019: 1-6 - [c6]Hanhe Lin, Vlad Hosu, Dietmar Saupe:
KADID-10k: A Large-scale Artificially Distorted IQA Database. QoMEX 2019: 1-3 - [c5]Hui Men, Hanhe Lin, Vlad Hosu, Daniel Maurer, Andrés Bruhn, Dietmar Saupe:
Visual Quality Assessment for Motion Compensated Frame Interpolation. QoMEX 2019: 1-6 - [i5]Hui Men, Hanhe Lin, Vlad Hosu, Daniel Maurer, Andrés Bruhn, Dietmar Saupe:
Technical Report on Visual Quality Assessment for Frame Interpolation. CoRR abs/1901.05362 (2019) - [i4]Vlad Hosu, Bastian Goldlücke, Dietmar Saupe:
Effective Aesthetics Prediction with Multi-level Spatially Pooled Features. CoRR abs/1904.01382 (2019) - [i3]Vlad Hosu, Hanhe Lin, Tamás Szirányi, Dietmar Saupe:
KonIQ-10k: An ecologically valid database for deep learning of blind image quality assessment. CoRR abs/1910.06180 (2019) - [i2]Franz Götz-Hahn, Vlad Hosu, Hanhe Lin, Dietmar Saupe:
No-Reference Video Quality Assessment using Multi-Level Spatially Pooled Features. CoRR abs/1912.07966 (2019) - 2018
- [c4]Vlad Hosu, Hanhe Lin, Dietmar Saupe:
Expertise screening in crowdsourcing image quality. QoMEX 2018: 1-6 - [c3]Oliver Wiedemann, Vlad Hosu, Hanhe Lin, Dietmar Saupe:
Disregarding the Big Picture: Towards Local Image Quality Assessment. QoMEX 2018: 1-6 - [i1]Hanhe Lin, Vlad Hosu, Dietmar Saupe:
KonIQ-10k: Towards an ecologically valid and large-scale IQA database. CoRR abs/1803.08489 (2018) - 2017
- [c2]Vlad Hosu, Franz Hahn, Mohsen Jenadeleh, Hanhe Lin, Hui Men, Tamás Szirányi, Shujun Li, Dietmar Saupe:
The Konstanz natural video database (KoNViD-1k). QoMEX 2017: 1-6 - 2016
- [c1]Vlad Hosu, Franz Hahn, Oliver Wiedemann, Sung-Hwan Jung, Dietmar Saupe:
Saliency-driven image coding improves overall perceived JPEG quality. PCS 2016: 1-5 - 2014
- [j1]Vlad Hosu, Mai Lan Ha, Terence Sim:
Light montage for perceptual image enhancement. Comput. Graph. Forum 33(2): 185-194 (2014)
Coauthor Index
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