ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes
ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes
Exploiting synthetic data to learn deep models has attracted increasing attention in recent years. However, the intrinsic domain difference between synthetic and real images usually causes a significant performance drop when applying the learned model to real world scenarios. This is mainly due to two reasons: 1) the model overfits …