Abstract

Letting a deep network be aware of the quality of its own predictions is an interesting yet important problem. In the task of instance segmentation, the confidence of instance classification is used as mask quality score in most instance segmentation frameworks. However, the mask quality, quantified as the IoU between the instance mask and its ground truth, is usually not well correlated with classification score. In this paper, we study this problem and propose Mask Scoring R-CNN which contains a network block to learn the quality of the predicted instance masks. The proposed network block takes the instance feature and the corresponding predicted mask together to regress the mask IoU. The mask scoring…

Citation impact

1,066
total citations
FWCI
59.09
Percentile
100%
References
58
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Segmentation
  • Block (permutation group theory)
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Feature (linguistics)
  • Ground truth
  • Task (project management)
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