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Fig. 3.

ID: ZDB-IMAGE-230916-91
Source: Figures for Lauenburg et al., 2023

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Fig. 3.

Different segmentation losses for two domains. (a) For an annotated image in X, we compute the supervised losses of predicted segmentation representations against the label. (b) For an unlabeled image in Y, we enforce structural consistency between predicted representations (as the underlying structures should be shared) and also segmentation-based adversarial losses to improve the quality of predictions in the absence of paired labels.

Acknowledgments

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