  We present MeshLeTemp, a powerful method for 3D human pose and mesh
reconstruction from a single image. In terms of human body priors encoding, we
propose using a learnable template human mesh instead of a constant template as
utilized by previous state-of-the-art methods. The proposed learnable template
reflects not only vertex-vertex interactions but also the human pose and body
shape, being able to adapt to diverse images. We conduct extensive experiments
to show the generalizability of our method on unseen scenarios.
