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cs.CV2024
Memory-Efficient Pseudo-Labeling for Online Source-Free Universal Domain Adaptation using a Gaussian Mixture Model
Pascal Schlachter, Simon Wagner, Bin Yang
In practice, domain shifts are likely to occur between training and test data, necessitating domain adaptation (DA) to adjust the pre-trained source model to the target domain. Rec…
cs.CV2024
COMET: Contrastive Mean Teacher for Online Source-Free Universal Domain Adaptation
Pascal Schlachter, Bin Yang
In real-world applications, there is often a domain shift from training to test data. This observation resulted in the development of test-time adaptation (TTA). It aims to adapt a…