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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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Panoptic Segmentation Cityscapes val CRF + PSPNet (ResNet-101) PQ 53.8 # 12
Panoptic Segmentation Cityscapes val CRF + PSPNet (ResNet-101) PQst 62.1 # 9
Panoptic Segmentation Cityscapes val CRF + PSPNet (ResNet-101) PQth 42.5 # 11
Panoptic Segmentation Cityscapes val CRF + PSPNet (ResNet-101) mIoU 71.6 # 8