RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features

@article{Zhang2021RefineMaskTH,
  title={RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features},
  author={Gang Zhang and Xin Lu and Jingru Tan and Jianmin Li and Zhaoxiang Zhang and Quanquan Li and Xiaolin Hu},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={6857-6865}
}
  • Gang ZhangXin Lu Xiaolin Hu
  • Published 17 April 2021
  • Computer Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
The two-stage methods for instance segmentation, e.g. Mask R-CNN, have achieved excellent performance recently. However, the segmented masks are still very coarse due to the downsampling operations in both the feature pyramid and the instance-wise pooling process, especially for large objects. In this work, we propose a new method called RefineMask for high-quality instance segmentation of objects and scenes, which incorporates fine-grained features during the instance-wise segmenting process… 

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