Controllable Person Image Synthesis With Attribute-Decomposed GAN

@article{Men2020ControllablePI,
  title={Controllable Person Image Synthesis With Attribute-Decomposed GAN},
  author={Yifang Men and Yiming Mao and Yuning Jiang and Wei-Ying Ma and Zhouhui Lian},
  journal={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020},
  pages={5083-5092}
}
  • Yifang Men, Yiming Mao, Zhouhui Lian
  • Published 27 March 2020
  • Computer Science
  • 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e.g., pose, head, upper clothes and pants) provided in various source inputs. The core idea of the proposed model is to embed human attributes into the latent space as independent codes and thus achieve flexible and continuous control of attributes via mixing and interpolation operations in explicit style… 

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