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Publikační činnost 2024

Články v ostatních periodikách

JANOUŠKOVÁ, K. et al. Single Image Test-Time Adaptation for Segmentation. Transactions on Machine Learning Research. 2024, ISSN 2835-8856. Dostupné z: https://openreview.net/forum?id=68LsWm2GuD

Stati ve sbornících konferencí

PAPLHÁM, J. a V. FRANC. A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). USA: IEEE Computer Society, 2024. DOI 10.1109/CVPR52733.2024.00120.

STOJNIĆ, V., Z. LASKAR a G. TOLIAS. Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning. In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, HI, USA, 2024-01-04/2024-01-08. Piscataway: IEEE, 2024. s. 259-268. ISSN 2642-9381. ISBN 979-8-3503-1892-0. DOI 10.1109/WACV57701.2024.00033. Dostupné z: https://openaccess.thecvf.com/content/WACV2024/papers/Stojnic_Training_Ensembles_With_Inliers_and_Outliers_for_Semi-Supervised_Active_Learning_WACV_2024_paper.pdf

ČERMÁK, V. et al. WildlifeDatasets: An Open-source Toolkit for Animal Re-identification. In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, HI, USA, 2024-01-04/2024-01-08. Piscataway: IEEE, 2024. s. 5941-5951. ISSN 2642-9381. ISBN 979-8-3503-1892-0. DOI 10.1109/WACV57701.2024.00585. Dostupné z: https://openaccess.thecvf.com/content/WACV2024/papers/Cermak_WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification_WACV_2024_paper.pdf

ŠPETLÍK, R., D. ROZUMNYI a J. MATAS. Single-Image Deblurring, Trajectory and Shape Recovery of Fast Moving Objects with Denoising Diffusion Probabilistic Models. In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, HI, USA, 2024-01-04/2024-01-08. Piscataway: IEEE, 2024. ISSN 2642-9381. ISBN 979-8-3503-1892-0.

JELÍNEK, T., J. ŠERÝCH a J. MATAS. Dense Matchers for Dense Tracking. In: Proceedings of the 27th Computer Vision Winter Workshop. 27th Computer Vision Winter Workshop, Terme Olimia, 2024-02-14/2024-02-16. Ljubljana: Slovenian Pattern Recognition Society, 2024. s. 18-28. ISBN 978-961-96564-0-2. Dostupné z: https://cvww2024.sdrv.si/proceedings/

ADAM, L. et al. SeaTurtleID2022: A Long-span Dataset for Reliable Sea Turtle Re-identification. In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, HI, USA, 2024-01-04/2024-01-08. Piscataway: IEEE, 2024. s. 7131-7141. ISSN 2642-9381. ISBN 979-8-3503-1892-0. DOI 10.1109/WACV57701.2024.00699. Dostupné z: https://openaccess.thecvf.com/content/WACV2024/html/Adam_SeaTurtleID2022_A_Long-Span_Dataset_for_Reliable_Sea_Turtle_Re-Identification_WACV_2024_paper.html

STOJNIĆ, V., Y. KALANTIDIS a G. TOLIAS. Label Propagation for Zero-shot Classification with Vision-Language Models. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, 2024-06-16/2024-06-22. Los Alamitos: IEEE Computer Society, 2024. s. 23209-23218. ISSN 2575-7075. ISBN 979-8-3503-5300-6. DOI 10.1109/CVPR52733.2024.02190. Dostupné z: https://openaccess.thecvf.com/content/CVPR2024/papers/Stojni_Label_Propagation_for_Zero-shot_Classification_with_Vision-Language_Models_CVPR_2024_paper.pdf

ŠUBRTOVÁ, A., J. ČECH a A. SUGIMOTO. Detecting and Correcting Perceptual Artifacts in Synthetic Face Images. In: Proceedings of the 27th Computer Vision Winter Workshop. 27th Computer Vision Winter Workshop, Terme Olimia, 2024-02-14/2024-02-16. Ljubljana: Slovenian Pattern Recognition Society, 2024. s. 38-46. ISBN 978-961-96564-0-2. Dostupné z: https://cvww2024.sdrv.si/wp-content/uploads/sites/5/2024/02/CVWW2024_Proceedings.pdf

NEORAL, M., J. ŠERÝCH a J. MATAS. MFT: Long-Term Tracking of Every Pixel. In: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Waikoloa, HI, USA, 2024-01-04/2024-01-08. Piscataway: IEEE, 2024. s. 6823-6833. ISSN 2642-9381. ISBN 979-8-3503-1892-0. DOI 10.1109/WACV57701.2024.00669. Dostupné z: https://ieeexplore.ieee.org/document/10484299