A simple preprocessing approach for improving semantic segmentation in unsupervised domain adaptation

A simple preprocessing approach for improving semantic segmentation in unsupervised domain adaptation

Abstract Unsupervised Domain Adaptation (UDA) is a powerful strategy for bridging the gap between synthetic (source) data and real-world (target) data, thereby reducing expensive manual annotations. In this work, we propose ProCST, a novel preprocessing framework that translates source images into t...

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Bibliographic Details
Main Authors: Shahaf Ettedgui, Shady Abu-Hussein, Raja Giryes
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Domain Adaptation
Semantic Segmentation
Sim2real
Online Access:https://doi.org/10.1038/s41598-025-05368-4
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https://doi.org/10.1038/s41598-025-05368-4

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