Semantic Foreground Inpainting From Weak Supervision

@article{Lu2020SemanticFI,
  title={Semantic Foreground Inpainting From Weak Supervision},
  author={Chenyang Lu and Gijs Dubbelman},
  journal={IEEE Robotics and Automation Letters},
  year={2020},
  volume={5},
  pages={1334-1341}
}
  • Chenyang Lu, Gijs Dubbelman
  • Published 2020
  • Computer Science
  • IEEE Robotics and Automation Letters
  • Semantic scene understanding is an essential task for self-driving vehicles and mobile robots. In our work, we aim to estimate a semantic segmentation map, in which the foreground objects are removed and semantically inpainted with background classes, from a single RGB image. This semantic foreground inpainting task is performed by a single-stage convolutional neural network (CNN) that contains our novel max-pooling as inpainting (MPI) module, which is trained with weak supervision, i.e., it… CONTINUE READING

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