REBASE: Reference-Background Subspace Elimination for Training-Free In-Context Segmentation
REBASE is a training-free method for in-context segmentation that introduces new object categories at inference time using only one reference image. It works by removing confusing background context from features using an orthogonal projection onto the complement of a low-rank background subspace derived from the reference image, leading to more accurate segmentation.