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Biography
Francesco Barbato is a Ph.D. student in Information Engineering at the Department of Information Engineering of the University of Padua.
He received his BS in Information Engineering and MS in ICT for Internet and Multimedia (with honors) from the University of Padua respectively in 2018 and 2020.
His research activities focus on Machine Learning techniques for Computer Vision, particularly in unsupervised domain adaptation, unsupervised continual learning, multimodal learning and continual learning for semantic segmentation and image classification.
Research interests
His research interests are:
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Unsupervised Domain Adaptation
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Continual Learning
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Multimodal Learning
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Semantic Segmentation
Publications
Journals:
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Shenaj D., Barbato F., Michieli U. and Zanuttigh P.,
Continual Coarse-to-Fine Domain Adaptation in Semantic Segmentation, Elsevier Image and Vision Computing (IMAVIS), 2022.
Conference proceedings:
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F. Barbato, M. Toldo, U. Michieli, P. Zanuttigh,
Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation,
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, p. 2835-2845, 2021.
Archive Pre-Prints:
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P. Testolina, F. Barbato, U. Michieli, M. Giordani, P. Zanuttigh, M. Zorzi,
SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints,
arXiv preprint arXiv:2204.09788, 2022.
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F. Barbato, U. Michieli, M. Toldo, P. Zanuttigh,
Adapting Segmentation Networks to New Domains by Disentangling Latent Representations,
arXiv preprint arXiv:2108.03021, 2021.
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