This repo is the source code for End-to-end Hand Mesh Recovery from a Monocular RGB Image by Xiong Zhang, Qiang Li, Webnbo Zhang, and Wen Zheng. HAMR targets at tackle the problem of reconstructing the full 3D mesh of a human hand from a single RGB image. In contrast to existing research on 2D or 3D hand pose estimation from RGB or/and depth image data, HAMR can provide a more expressive and useful mesh representation for monocular hand image understanding. In particular, the mesh representation is achieved by parameterizing a generic 3D hand model with shape and relative 3D joint angles.