FSNet: A Failure Detection Framework for Semantic Segmentation

@article{Rahman2021FSNetAF,
  title={FSNet: A Failure Detection Framework for Semantic Segmentation},
  author={Q. Rahman and Niko Sunderhauf and Peter Corke and Feras Dayoub},
  journal={IEEE Robotics and Automation Letters},
  year={2021},
  volume={PP},
  pages={1-1}
}
Semantic segmentation is an important task that helps autonomous vehicles understand their surroundings and navigate safely. However, during deployment, even the most mature segmentation models are vulnerable to various external factors that can degrade the segmentation performance with potentially catastrophic consequences for the vehicle and its surroundings. To address this issue, we propose a failure detection framework to identify pixel-level misclassification. We do so by exploiting… 

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