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Four typical network structures for pose-guided person image generation. (a) Top-down method directly concatenates í µí°¼ í µí± , í µí± í µí± and í µí± í µí±¡ as input to synthesize í µí°¼ í µí±¡ . (b) Bottom-up latent feature representation method extracts the source appearance feature í µí± í µí°ánd target pose feature í µí± í µí± as internal representations. (c) Bottom-up deformation method tries to deform the feature maps of í µí°¼ í µí± and í µí± í µí± into the target pose í µí± í µí±¡ . (d) Hybrid method fuses the top-down and bottom-up deformation methods into a framework.
Source publication
Deep person generation has attracted extensive research attention due to its wide applications in virtual agents, video conferencing, online shopping and art/movie production. With the advancement of deep learning, visual appearances (face, pose, cloth) of a person image can be easily generated or manipulated on demand. In this survey, we first sum...
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