Recursive Training for Zero-Shot Semantic Segmentation

@article{Wang2021RecursiveTF,
  title={Recursive Training for Zero-Shot Semantic Segmentation},
  author={Ce Wang and Moshiur Rahman Farazi and Nick Barnes},
  journal={2021 International Joint Conference on Neural Networks (IJCNN)},
  year={2021},
  pages={1-8}
}
  • Ce Wang, M. Farazi, N. Barnes
  • Published 26 February 2021
  • Computer Science
  • 2021 International Joint Conference on Neural Networks (IJCNN)
General purpose semantic segmentation relies on a backbone CNN network to extract discriminative features that help classify each image pixel into a ‘seen’ object class (i.e., the object classes available during training) or a background class. Zero-shot semantic segmentation is a challenging task that requires a computer vision model to identify image pixels belonging to an object class which it has never seen before. Equipping a general purpose semantic segmentation model to separate image… 

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