SynthGenNet reports 49.79 mIoU on IDD and 48.33 on Cityscapes by mixing multiple synthetic sources with diverse self-supervised losses, but the method actually uses unlabeled target images during training, so it is not domain generalization.
Cutmix: Regularization strategy to train strongclas- sifiers with localizable features
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SynthGenNet: a self-supervised approach for test-time generalization using synthetic multi-source domain mixing of street view images
SynthGenNet reports 49.79 mIoU on IDD and 48.33 on Cityscapes by mixing multiple synthetic sources with diverse self-supervised losses, but the method actually uses unlabeled target images during training, so it is not domain generalization.