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In this paper, we present an interactive approach for shape co-segmentation via label propagation. Our intuitive approach is able to produce error-free results and is very effective at handling out-of-sample data. Specifically, we start by over-segmenting a set of shapes into primitive patches. Then, we allow the users to assign labels to some patches and propagate the label information from these patches to the unlabeled ones. We iterate the last two steps until the error-free consistent segmentations are obtained. Additionally, we provide an inductive extension of our framework, which effectively addresses the out-of-sample data. The experimental results demonstrate the effectiveness of our approach.