preprintJun 1, 2019Closed access

Hybrid Task Cascade for Instance Segmentation

Chinese University of Hong Kong · The University of Sydney · +4 more institutions

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Abstract

Cascade is a classic yet powerful architecture that has boosted performance on various tasks. However, how to introduce cascade to instance segmentation remains an open question. A simple combination of Cascade R-CNN and Mask R-CNN only brings limited gain. In exploring a more effective approach, we find that the key to a successful instance segmentation cascade is to fully leverage the reciprocal relationship between detection and segmentation. In this work, we propose a new framework, Hybrid Task Cascade (HTC), which differs in two important aspects: (1) instead of performing cascaded refinement on these two tasks separately, it interweaves them for a joint multi-stage processing; (2) it adopts a fully…

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1,486
total citations
FWCI
74.30
Percentile
100%
References
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Authors

12

Topics & keywords

Keywords
  • Computer science
  • Cascade
  • Segmentation
  • Discriminative model
  • Artificial intelligence
  • Leverage (statistics)
  • Pattern recognition (psychology)
  • Convolutional neural network
UN Sustainable Development Goals
  • Reduced inequalities
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