DG algorithms face fundamental challenges in FL setups due to the lack of samples/domains in each client's local dataset.

However, existing video classification models rely on the i.i.d.

Deep learning models have been widely used to assist doctors with clinical decision-making.

Images taken between 2013 and 2015 are used as the validation set.

Semi-Supervised Domain Generalization (SSDG) aims to learn a model that is generalizable to an unseen target domain with only a few labels, and most existing SSDG methods assume that unlabeled training and testing samples are all known classes. However, a more realistic scenario is that known classes may be mixed with some unknown classes in unlabeled training and testing data.