Click'n'Cut: Crowdsourced Interactive Segmentation with Object Candidates.

This paper introduces Click'n'Cut, a novel web tool for interactive object segmentation designed for crowdsourcing tasks. Click'n'Cut combines bounding boxes and clicks generated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that allows an immediate response from the interface. Click'n'Cut has been tested with a crowdsourcing campaign to annotate images from publicly available datasets. Results are competitive with state-of-the-art approaches, especially in terms of time needed to converge to a high quality segmentation.