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REBASE: Reference-Background Subspace Elimination for Training-Free In-Context Segmentation
Training-free in-context segmentation enables new object categories to be introduced at inference time from a single annotated reference image, eliminating the retraining and memory overhead of class-incremental learning. Recent approaches achieve this by combining vision foundation models for seman