AI RESEARCH
Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation
arXiv CS.CV
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ArXi:2302.01516v3 Announce Type: replace Current methods of blended targets domain adaptation (BTDA) usually infer or consider domain label information but underemphasize hybrid categorical feature structures of targets, which yields limited performance, especially under the label distribution shift. We nstrate that domain labels are not directly necessary for BTDA if categorical distributions of various domains are sufficiently aligned even facing the imbalance of domains and the label distribution shift of classes.