Learning Deep Structured Active Contours End-to-End

@article{Marcos2018LearningDS,
  title={Learning Deep Structured Active Contours End-to-End},
  author={Diego Marcos and D. Tuia and Benjamin Kellenberger and L. Zhang and Min Bai and Renjie Liao and R. Urtasun},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={8877-8885}
}
The world is covered with millions of buildings, and precisely knowing each instance's position and extents is vital to a multitude of applications. Recently, automated building footprint segmentation models have shown superior detection accuracy thanks to the usage of Convolutional Neural Networks (CNN). However, even the latest evolutions struggle to precisely delineating borders, which often leads to geometric distortions and inadvertent fusion of adjacent building instances. We propose to… Expand
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