Simplified unsupervised image translation for semantic segmentation adaptation

Highlights：

• A simple yet effective unsupervised image translation method (SUIT)is proposed for domain adaptation on semantic segmentation, which avoids labor-intensive pixel-wise annotation.

• The decoupled model design makes it moreflexible; the adaptation network be easily transplanted to other segmentation networks without repeating the adaptation process.

• A model average skill is developed to improve the performance in domain adaptation context. The effectiveness of our proposed model is verified on multiple synthetic-to-real adaptation benchmarks.