Further, we introduce two complementary losses which explicitly regularize the semantic structure of thefeature space.

In the United States, health insurance is a critical component of individuals' ability to access health care.

We quantify the drop in PEBAL's performance with the added domain shift and compare it to the performance when combined with our method or existing test-time adaptation methods such as

In open-world scenarios, where both novel classes and domains may exist, an ideal segmentation model should detect anomaly classes for safety and generalize to new domains.

Inthe forward step, CST generates target pseudo-labels with asource-trained classifier.