Unsupervised Domain Adaptation in Semantic Segmentation: a Review

Understand

The aim of this paper is to give an overview of the recent advancements in the Unsupervised Domain Adaptation (UDA) of deep networks for semantic segmentation.

• This task is attracting a wide interest, since semantic segmentation models require a huge amount of labeled data and the lack of data fitting specific requirements is the main limitation in the deployment of these techniques.
• This problem has been recently explored and has rapidly grown with a large number of ad-hoc approaches.
• This motivates us to build a comprehensive overview of the proposed methodologies and to provide a clear categorization.