Human motion transfer is challenging due to the complexity and diversity of human motion and clothing textures. Existing methods use 2D pose estimation to obtain poses, which can easily lead to unsmooth motion and artifacts. Therefore, this paper proposes a highly robust motion transmission model based on image deformation, called the Filter-Deform Attention Generative Adversarial Network (FDA GAN). This method can transmit complex human motion videos using only few human images. First, we use a 3D pose shape estimator instead of traditional 2D pose estimation to address the problem of unsmoot...
