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Detect objects in new domain without labels in target by using domain-invariant frequencies with FIT

Detect objects in new domain without labels in target by using domain-invariant frequencies with FIT


FIT: Frequency-based Image Translation for Domain Adaptive Object Detection

arXiv paper abstract https://arxiv.org/abs/2303.03698



Domain adaptive object detection (DAOD) aims to adapt the detector from a labelled source domain to an unlabelled target domain.


... propose a novel Frequency-based Image Translation (FIT) framework for DAOD.


First, by keeping domain-invariant frequency components and swapping domain-specific ones, ... conduct image translation to reduce domain shift at the input level.


Second, hierarchical adversarial feature learning is utilized to further mitigate the domain gap at the feature level.


Finally, ... design a joint loss to train the entire network in an end-to-end manner without extra training to obtain translated images.


... demonstrate the effectiveness of ... method.



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