Weakly- and Semi-Supervised Panoptic Segmentation

ECCV 2018 Qizhu LiAnurag ArnabPhilip H. S. Torr

We present a weakly supervised model that jointly performs both semantic- and instance-segmentation -- a particularly relevant problem given the substantial cost of obtaining pixel-perfect annotation for these tasks. In contrast to many popular instance segmentation approaches based on object detectors, our method does not predict any overlapping instances... (read more)

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