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The extent to which 3D samples from the predicted distribution match the We show that these approaches exhibit a trade-offīetween three key properties: (i) accuracy - the likelihood of the ground-truthģD solution under the predicted distribution, (ii) sample-input consistency. Predict a probability distribution over plausible 3D pose and shape parametersĬonditioned on the image. Multiple 3D solutions can explain a 2D image of a subject. Download a PDF of the paper titled HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation, by Akash Sengupta and Ignas Budvytis and Roberto Cipolla Download PDF Abstract: Monocular 3D human pose and shape estimation is an ill-posed problem since
