Interactive Image Segmentation with Latent Diversity

@article{Li2018InteractiveIS,
  title={Interactive Image Segmentation with Latent Diversity},
  author={Zhuwen Li and Qifeng Chen and Vladlen Koltun},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={577-585}
}
Interactive image segmentation is characterized by multimodality. When the user clicks on a door, do they intend to select the door or the whole house? We present an end-to-end learning approach to interactive image segmentation that tackles this ambiguity. Our architecture couples two convolutional networks. The first is trained to synthesize a diverse set of plausible segmentations that conform to the user's input. The second is trained to select among these. By selecting a single solution… 

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