Search Results for author: Jan Eric Lenssen

Found 9 papers, 7 papers with code

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

no code implementations27 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.


TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinement

no code implementations16 May 2022 Keyang Zhou, Bharat Lal Bhatnagar, Jan Eric Lenssen, Gerard Pons-Moll

The core of our method are TOCH fields, a novel spatio-temporal representation for modeling correspondences between hands and objects during interaction.

Denoising Object Reconstruction

Quaternion Equivariant Capsule Networks for 3D Point Clouds

2 code implementations ECCV 2020 Yongheng Zhao, Tolga Birdal, Jan Eric Lenssen, Emanuele Menegatti, Leonidas Guibas, Federico Tombari

We present a 3D capsule module for processing point clouds that is equivariant to 3D rotations and translations, as well as invariant to permutations of the input points.

Pose Estimation

Deep Iterative Surface Normal Estimation

2 code implementations CVPR 2020 Jan Eric Lenssen, Christian Osendorfer, Jonathan Masci

This results in a state-of-the-art surface normal estimator that is robust to noise, outliers and point density variation, preserves sharp features through anisotropic kernels and equivariance through a local quaternion-based spatial transformer.

Surface Normal Estimation Surface Normals Estimation

Fast Graph Representation Learning with PyTorch Geometric

4 code implementations6 Mar 2019 Matthias Fey, Jan Eric Lenssen

We introduce PyTorch Geometric, a library for deep learning on irregularly structured input data such as graphs, point clouds and manifolds, built upon PyTorch.

Graph Classification Graph Representation Learning +2

Group Equivariant Capsule Networks

1 code implementation NeurIPS 2018 Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski

We present group equivariant capsule networks, a framework to introduce guaranteed equivariance and invariance properties to the capsule network idea.

SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels

5 code implementations CVPR 2018 Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Müller

We present Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e. g., graphs or meshes.

General Classification Graph Classification +2

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