Disentangling Latent Hands for Image Synthesis and Pose Estimation

CVPR 2019 Linlin YangAngela Yao

Hand image synthesis and pose estimation from RGB images are both highly challenging tasks due to the large discrepancy between factors of variation ranging from image background content to camera viewpoint. To better analyze these factors of variation, we propose the use of disentangled representations and a disentangled variational autoencoder (dVAE) that allows for specific sampling and inference of these factors... (read more)

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