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Apr, 2021
自监督增强一致性用于语义分割适应
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation
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Nikita Araslanov, Stefan Roth
TL;DR
本研究提出一种实用且高精度的“领域自适应（domain adaptation）语义分割”方法，通过数据增强，确保保持图像转换后的语义预测的一致性，在轻量级自监督框架中训练并取得了显著的精度提高。
Abstract
We propose an approach to
domain adaptation
for
semantic segmentation
that is both practical and highly accurate. In contrast to previous work, we abandon the use of computationally involved adversarial objective
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