Active Boundary Loss for Semantic Segmentation

@inproceedings{Wang2021ActiveBL,
  title={Active Boundary Loss for Semantic Segmentation},
  author={Chi Wang and Yunke Zhang and Miaomiao Cui and Jinlin Liu and Peiran Ren and Yin Yang and Xuansong Xie and Xiansheng Hua and Hujun Bao and Weiwei Xu},
  booktitle={AAAI Conference on Artificial Intelligence},
  year={2021}
}
This paper proposes a novel active boundary loss for semantic segmentation. It can progressively encourage the alignment between predicted boundaries and ground-truth boundaries during end-to-end training, which is not explicitly enforced in commonly used cross-entropy loss. Based on the predicted boundaries detected from the segmentation results using current network parameters, we formulate the boundary alignment problem as a differentiable direction vector prediction problem to guide the… 
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