Umberto Michieli

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Pietro ZanuttighUniversity of PadovaVerified email at dei.unipd.it
Marco ToldoPhD at University of PadovaVerified email at phd.unipd.it
Francesco BarbatoPost Doc, Ph.D. in Information Engineering, University of PadovaVerified email at unipd.it
Andrea MaracaniAI Researcher, SamsungVerified email at samsung.com
Gianluca AgrestiSony R&D Center Europe Stuttgart Laboratory 1Verified email at sony.com
Leonardo BadiaAssociate Professor of Telecommunications, University of Padova, ItalyVerified email at unipd.it
Donald ShenajSamsung Research UKVerified email at samsung.com
Alessandro MuscoloniSenior AI Scientist, Ada HealthVerified email at ada.com
Carlo Vittorio CannistraciChair Professor & Chief Scientist, Center for Complex Network Intelligence, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
Ji Joong MoonSamsung ResearchVerified email at samsung.com
Elena CamuffoUniversity of PadovaVerified email at unipd.it
Simone MilaniAssociate Professor, University of Padova, Padova, ItalyVerified email at dei.unipd.it
Yingtao ZhangPhD student of Computer Science, Tsinghua UniversityVerified email at mails.tsinghua.edu.cn
Michele ZorziDept. of Information Engineering - University of Padova, ItalyVerified email at dei.unipd.it
Marco GiordaniAssociate Professor, University of PadovaVerified email at unipd.it
Paolo TestolinaNortheastern UniversityVerified email at northeastern.edu
Eros FanìPolitecnico di Torino, University of SussexVerified email at polito.it
Barbara CaputoDAUIN, Politecnico di TorinoVerified email at polito.it
Marco CicconePostdoctoral Fellow, Vector InstituteVerified email at vectorinstitute.ai
Debora CaldarolaPhD student @ Stanford University & Politecnico di TorinoVerified email at polito.it

Umberto Michieli

Samsung Research UK

Verified email at samsung.com - Homepage

Continual Learning Domain Adaptation Federated Learning Scene Understanding Model Compression


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Incremental Learning Techniques for Semantic Segmentation U Michieli, P Zanuttigh Proceedings of the International Conference on Computer Vision (ICCV …, 2019	280	2019
Unsupervised domain adaptation in semantic segmentation: a review M Toldo, A Maracani, U Michieli, P Zanuttigh Technologies 8 (2), 35, 2020	219	2020
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations U Michieli, P Zanuttigh CVPR, 2021	173	2021
RECALL: Replay-based Continual Learning in Semantic Segmentation A Maracani, U Michieli, M Toldo*, P Zanuttigh ICCV, 2021	142	2021
Knowledge distillation for incremental learning in semantic segmentation U Michieli, P Zanuttigh Computer Vision and Image Understanding, 103167, 2021	110	2021
Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation U Michieli, M Biasetton, G Agresti, P Zanuttigh IEEE Transactions on Intelligent Vehicles (T-IV), 2020	70	2020
Game theoretic analysis of road user safety scenarios involving autonomous vehicles U Michieli, L Badia 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile …, 2018	57	2018
Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings M Toldo, U Michieli, P Zanuttigh WACV, 2021	52	2021
Unsupervised Domain Adaptation for Mobile Semantic Segmentation based on Cycle Consistency and Feature Alignment M Toldo, U Michieli, G Agresti, P Zanuttigh Elsevier Image and Vision Computing, 2020	50	2020
Unsupervised Domain Adaptation for Semantic Segmentation of Urban Scenes M Biasetton, U Michieli, G Agresti, P Zanuttigh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	49	2019
Federated Learning via Attentive Margin of Semantic Feature Representations U Michieli, M Ozay IEEE Internet of Things Journal, 2022	48*	2022
GMNet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild U Michieli, E Borsato, L Rossi, P Zanuttigh ECCV, 2020	47	2020
Selma: Semantic large-scale multimodal acquisitions in variable weather, daytime and viewpoints P Testolina, F Barbato, U Michieli, M Giordani, P Zanuttigh, M Zorzi IEEE Transactions on Intelligent Transportation Systems 24 (7), 7012-7024, 2023	39	2023
Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning D Shenaj, E Fanì, M Toldo, D Caldarola, A Tavera, U Michieli, M Ciccone, ... WACV 2023, 2023	38	2023
Are all users treated fairly in federated learning systems? U Michieli, M Ozay Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021	35	2021
Local-ring network automata and the impact of hyperbolic geometry in complex network link-prediction A Muscoloni, U Michieli, CV Cannistraci arXiv preprint arXiv:1707.09496, 2017	30	2017
Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation F Barbato, M Toldo, U Michieli, P Zanuttigh CVPRW WAD, 2021	27	2021
Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training T Spadotto, M Toldo, U Michieli, P Zanuttigh ICPR, 2020	25	2020
Adaptive network automata modelling of complex networks A Muscoloni, U Michieli, Y Zhang, CV Cannistraci Preprints, 2022	22	2022
Continual Coarse-to-Fine Domain Adaptation in Semantic Segmentation D Shenaj, F Barbato, U Michieli, P Zanuttigh Elsevier Image and Vision Computing, 2022	15	2022

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