Single-Shot 3D Mesh Estimation via Adversarial Domain Adaptation

We present an adversarial deep domain adaptation (ADA) approach for training deep neural networks that estimate 3D pose and shape of a human from a single image. Existing datasets of in-the-wild images of humans have limited availability of 3D ground truth. We propose a novel deep architecture for 3D pose estimation and leverage the variations in pose, body shape and background in the synthetic datasets to train our network. Using ADA we adapt...