Unsupervised Person Image Synthesis in Arbitrary Poses

@article{Pumarola2018UnsupervisedPI,
  title={Unsupervised Person Image Synthesis in Arbitrary Poses},
  author={Albert Pumarola and Antonio Agudo and Alberto Sanfeliu and Francesc Moreno-Noguer},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={8620-8628}
}
We present a novel approach for synthesizing photorealistic images of people in arbitrary poses using generative adversarial learning. Given an input image of a person and a desired pose represented by a 2D skeleton, our model renders the image of the same person under the new pose, synthesizing novel views of the parts visible in the input image and hallucinating those that are not seen. This problem has recently been addressed in a supervised manner [16, 35], i.e., during training the ground… CONTINUE READING

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