Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach

CVPR 2019 Yuhua ChenWen LiXiaoran ChenLuc Van Gool

Recently, increasing attention has been drawn to training semantic segmentation models using synthetic data and computer-generated annotation. However, domain gap remains a major barrier and prevents models learned from synthetic data from generalizing well to real-world applications... (read more)

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