Learning to adapt class-specific features across domains for semantic segmentation

22 Jan 2020Mikel MentaAdriana RomeroJoost van de Weijer

Recent advances in unsupervised domain adaptation have shown the effectiveness of adversarial training to adapt features across domains, endowing neural networks with the capability of being tested on a target domain without requiring any training annotations in this domain. The great majority of existing domain adaptation models rely on image translation networks, which often contain a huge amount of domain-specific parameters... (read more)

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