Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields

1 code implementation • 27 Jul 2022 • Garvita Tiwari, Dimitrije Antic, Jan Eric Lenssen, Nikolaos Sarafianos, Tony Tung, Gerard Pons-Moll

The resulting high-dimensional implicit function can be differentiated with respect to the input poses and thus can be used to project arbitrary poses onto the manifold by using gradient descent on the set of 3-dimensional hyperspheres.

Denoising

On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks

2 code implementations • ICLR 2022 • Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius

In this work, we examine this approach and identify potential hazards associated with the use of log-likelihood in conjunction with gradient-based optimizers.