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cs.CV2024
Uncertainty-guided Open-Set Source-Free Unsupervised Domain Adaptation with Target-private Class Segregation
Mattia Litrico, Davide Talon, Sebastiano Battiato +3
Standard Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target but usually requires simultaneous access to both source…
cs.CV2024
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis
Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3
This study provides a comprehensive benchmark framework for Source-Free Unsupervised Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical unde…
cs.CV2022
GANzzle: Reframing jigsaw puzzle solving as a retrieval task using a generative mental image
Davide Talon, Alessio Del Bue, Stuart James
Puzzle solving is a combinatorial challenge due to the difficulty of matching adjacent pieces. Instead, we infer a mental image from all pieces, which a given piece can then be mat…