Hybrid Task Cascade for Instance Segmentation
Chinese University of Hong Kong · The University of Sydney · +4 more institutions
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…
Citation impact
- FWCI
- 74.30
- Percentile
- 100%
- References
- 64
Authors
12Topics & keywords
- Computer science
- Cascade
- Segmentation
- Discriminative model
- Artificial intelligence
- Leverage (statistics)
- Pattern recognition (psychology)
- Convolutional neural network
- Reduced inequalities