Fudan University

Tianyun Zou

Yanwei Fu

Xiangyang Xue

Yinda Zhang

Haitao Lin

Chao Wen

Jiashun Wang

A network for neural pose transfer includes a pose feature extractor, and a style transfer decoder, wherein the pose feature extractor comprises a plurality of sequential extracting stacks, each extracting stack consists of a first convolution layer and an Instance Norm layer sequential to the first convolution layer. The style transfer decoder comprises a plurality of sequential decoding stacks, a second convolution layer sequential to the plurality of decoding stacks and a tan h layer sequential to the second convolution layer. Each decoding stack consists of a third convolution layer and a SPAdaIn residual block. A source pose mesh is input to the pose feature extractor, and an identity mesh is concatenated with the output of the pose feature extractor and meanwhile fed to each SPAdaIn residual block of the style transfer decoder. A system thereof is also provided.

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Shanghai, China

Tianyun Zou