Publications

Mariia Zameshina, Olivier Teytaud, Fabien Teytaud, Vlad Hosu, Nathanael Carraz, Laurent Najman, and Markus Wagner. Fairness in generative modeling: do it unsupervised!. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 320--323, ACM, July 2022. [PUMA: sfbtrr161 a05 from:christinawarren 2022] URL

Shaolin Su, Hanhe Lin, Vlad Hosu, Oliver Wiedemann, Jinqiu Sun, Yu Zhu, Hantao Liu, Yanning Zhang, and Dietmar Saupe. Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model. CoRR, 2022. [PUMA: sfbtrr161 a05 from:christinawarren 2022] URL

Hanhe Lin, Hui Men, Yijun Yan, Jinchang Ren, and Dietmar Saupe. Crowdsourced Quality Assessment of Enhanced Underwater Images - a Pilot Study. Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX), 1--4, IEEE, September 2022. [PUMA: 2022 a05 from:christinawarren sfbtrr161] URL

Jianxun Lou, Hanhe Lin, David Marshall, Dietmar Saupe, and Hantao Liu. TranSalNet: Towards perceptually relevant visual saliency prediction. Neurocomputing, (494):455–467, 2022. [PUMA: sfbtrr161 a05 from:christinawarren 2022] URL

Hanhe Lin, Guangan Chen, Mohsen Jenadeleh, Vlad Hosu, Ulf-Dietrich Reips, Raouf Hamzaoui, and Dietmar Saupe. Large-Scale Crowdsourced Subjective Assessment of Picturewise Just Noticeable Difference. IEEE Transactions on Circuits and Systems for Video Technology, (32)9:5859-5873, 2022. [PUMA: sfbtrr161 a05 from:christinawarren 2022] URL

Franz Götz-Hahn, Vlad Hosu, and Dietmar Saupe. Critical Analysis on the Reproducibility of Visual Quality Assessment Using Deep Features. PLoS ONE, (17)82022. [PUMA: sfbtrr161 a05 from:christinawarren 2022] URL

Vlad Hosu, Hanhe Lin, Tamas Sziranyi, and Dietmar Saupe. KonIQ-10k : An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment. IEEE Transactions on Image Processing, (29):4041--4056, 2020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Shaolin Su, Vlad Hosu, Hanhe Lin, Yanning Zhang, and Dietmar Saupe. KonIQ++: Boosting No-Reference Image Quality Assessment in the Wild by Jointly Predicting Image Quality and Defects. 32nd British Machine Vision Conference, 1–12, 2021. [PUMA: sfbtrr161 a05 from:christinawarren 2021] URL

Hui Men, Hanhe Lin, Mohsen Jenadeleh, and Dietmar Saupe. Subjective Image Quality Assessment with Boosted Triplet Comparisons. IEEE Access, (9):138939-138975, IEEE, 2021. [PUMA: sfbtrr161 a05 from:christinawarren 2021] URL

Hanhe Lin, Guangan Chen, and Felix Wilhelm Siebert. Positional Encoding: Improving Class-Imbalanced Motorcycle Helmet use Classification. 2021 IEEE International Conference on Image Processing (ICIP), 1194-1198, 2021. [PUMA: sfbtrr161 a05 from:christinawarren 2021] URL

Hanhe Lin, Vlad Hosu, Chunling Fan, Yun Zhang, Yuchen Mu, Raouf Hamzaoui, and Dietmar Saupe. SUR-FeatNet: Predicting the Satisfied User Ratio Curvefor Image Compression with Deep Feature Learning. Quality and User Experience, (5)1:1–23, 2020. [PUMA: 2020 a05 from:christinawarren sfbtrr161] URL

Hui Men, Vlad Hosu, Hanhe Lin, Andrés Bruhn, and Dietmar Saupe. Subjective annotation for a frame interpolation benchmark using artefact amplification. Quality and User Experience, (5)12020. [PUMA: sfbtrr161 a05 b04 from:christinawarren 2020 visus visus:bruhnas] URL

Mohsen Jenadeleh, Marius Pedersen, and Dietmar Saupe. Blind Quality Assessment of Iris Images Acquired in Visible Light for Biometric Recognition. Sensors, (20)52020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Mai Lan Ha, Vlad Hosu, and Volker Blanz. Color Composition Similarity and Its Application in Fine-grained Similarity. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), 2548--2557, IEEE, Piscataway, NJ, 2020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Baptiste Roziere, Fabien Teytaud, Vlad Hosu, Hanhe Lin, Jeremy Rapin, Mariia Zameshina, and Olivier Teytaud. EvolGAN: Evolutionary Generative Adversarial Networks. Computer Vision -- ACCV 2020, 679--694, Springer International Publishing, Cham, November 2021. [PUMA: 2021 a05 from:christinawarren sfbtrr161] URL

Oliver Wiedemann, Vlad Hosu, Hanhe Lin, and Dietmar Saupe. Foveated Video Coding for Real-Time Streaming Applications. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX), 1-6, 2020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Xin Zhao, Hanhe Lin, Pengfei Guo, Dietmar Saupe, and Hantao Liu. Deep Learning VS. Traditional Algorithms for Saliency Prediction of Distorted Images. 2020 IEEE International Conference on Image Processing (ICIP), 156-160, 2020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Baptiste Roziere, Nathanaël Carraz Rakotonirina, Vlad Hosu, Andry Rasoanaivo, Hanhe Lin, Camille Couprie, and Olivier Teytaud. Tarsier: Evolving Noise Injection in Super-Resolution GANs. 2020 25th International Conference on Pattern Recognition (ICPR), 7028-7035, 2021. [PUMA: sfbtrr161 a05 from:christinawarren 2021] URL

Hanhe Lin, Jeremiah D. Deng, Deike Albers, and Felix Wilhelm Siebert. Helmet Use Detection of Tracked Motorcycles Using CNN-Based Multi-Task Learning. IEEE Access, (8):162073-162084, 2020. [PUMA: sfbtrr161 a05 from:christinawarren 2020] URL

Franz Götz-Hahn, Vlad Hosu, Hanhe Lin, and Dietmar Saupe. KonVid-150k : A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild. IEEE Access, (9):72139--72160, 2021. [PUMA: sfbtrr161 a05 from:christinawarren 2021] URL