Aming Wu

1. Learning to Adapt Structured Output
Space for Semantic Segmentation

2. Motivation
• This trained model may not generalize well to
unseen images, especially when there is a
domain gap between the training (source) and
test (target) images.
• To address this issue, knowledge transfer or
domain adaptation techniques have been
proposed to close the gap between source and
target domains, where annotations are not
available in the target domain.

4. Algorithmic Overview

7. Multi-level Adversarial Learning