Random image stylization as a training augmentation, combined with a two-stage training scheme, improves synthetic-to-real domain adaptation for semantic segmentation over conventional training.
Approximating CNNs with bag-of-local- features models works surprisingly well on imagenet,
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Texture Underfitting for Domain Adaptation
Random image stylization as a training augmentation, combined with a two-stage training scheme, improves synthetic-to-real domain adaptation for semantic segmentation over conventional training.