  We present a new method for few-shot human motion transfer that achieves
realistic human image generation with only a small number of appearance inputs.
Despite recent advances in single person motion transfer, prior methods often
require a large number of training images and take long training time. One
promising direction is to perform few-shot human motion transfer, which only
needs a few of source images for appearance transfer. However, it is
particularly challenging to obtain satisfactory transfer results. In this
paper, we address this issue by rendering a human texture map to a surface
geometry (represented as a UV map), which is personalized to the source person.
Our geometry generator combines the shape information from source images, and
the pose information from 2D keypoints to synthesize the personalized UV map. A
texture generator then generates the texture map conditioned on the texture of
source images to fill out invisible parts. Furthermore, we may fine-tune the
texture map on the manifold of the texture generator from a few source images
at the test time, which improves the quality of the texture map without
over-fitting or artifacts. Extensive experiments show the proposed method
outperforms state-of-the-art methods both qualitatively and quantitatively. Our
code is available at https://github.com/HuangZhiChao95/FewShotMotionTransfer.
