A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation

@article{Khare2020AGF,
  title={A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation},
  author={Varun Kumar Khare and Divyat Mahajan and Homanga Bharadhwaj and Vinay Kumar Verma and Piyush Rai},
  journal={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  year={2020},
  pages={3090-3099}
}
We present a domain adaptation based generative framework for zero-shot learning. Our framework addresses the problem of domain shift between the seen and unseen class distributions in zero-shot learning and minimizes the shift by developing a generative model trained via adversarial domain adaptation. Our approach is based on end-to-end learning of the class distributions of seen classes and unseen classes. To enable the model to learn the class distributions of unseen classes, we parameterize… 

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