Adversarial Learning for Semi-Supervised Semantic Segmentation

@article{Hung2018AdversarialLF,
  title={Adversarial Learning for Semi-Supervised Semantic Segmentation},
  author={Wei-Chih Hung and Yi-Hsuan Tsai and Yan-Ting Liou and Yen-Yu Lin and Ming-Hsuan Yang},
  journal={CoRR},
  year={2018},
  volume={abs/1802.07934}
}
We propose a method for semi-supervised semantic segmentation using an adversarial network. While most existing discriminators are trained to classify input images as real or fake on the image level, we design a discriminator in a fully convolutional manner to differentiate the predicted probability maps from the ground truth segmentation distribution with the consideration of the spatial resolution. We show that the proposed discriminator can be used to improve semantic segmentation accuracy… CONTINUE READING