  This paper proposes an approach that generates multiple 3D human meshes from
text. The human shapes are represented by 3D meshes based on the SMPL model.
The model's performance is evaluated on the COCO dataset, which contains
challenging human shapes and intricate interactions between individuals. The
model is able to capture the dynamics of the scene and the interactions between
individuals based on text. We further show how using such a shape as input to
image synthesis frameworks helps to constrain the network to synthesize humans
with realistic human shapes.
