MACS: Mass Conditioned 3D Hand and Object Motion Synthesis

no code implementations • 22 Dec 2023 • Soshi Shimada, Franziska Mueller, Jan Bednarik, Bardia Doosti, Bernd Bickel, Danhang Tang, Vladislav Golyanik, Jonathan Taylor, Christian Theobalt, Thabo Beeler

To improve the naturalness of the synthesized 3D hand object motions, this work proposes MACS the first MAss Conditioned 3D hand and object motion Synthesis approach.

Motion Synthesis Object

Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases

1 code implementation • 12 Nov 2021 • Jan Bednarik, Noam Aigerman, Vladimir G. Kim, Siddhartha Chaudhuri, Shaifali Parashar, Mathieu Salzmann, Pascal Fua

The key to making these correspondences semantically meaningful is to guarantee that the metric tensors computed at corresponding points are as similar as possible.

Surface Reconstruction

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

1 code implementation • ICCV 2021 • Jan Bednarik, Vladimir G. Kim, Siddhartha Chaudhuri, Shaifali Parashar, Mathieu Salzmann, Pascal Fua, Noam Aigerman

We propose a method for the unsupervised reconstruction of a temporally-coherent sequence of surfaces from a sequence of time-evolving point clouds, yielding dense, semantically meaningful correspondences between all keyframes.

Surface Reconstruction

Shape Reconstruction by Learning Differentiable Surface Representations

1 code implementation • CVPR 2020 • Jan Bednarik, Shaifali Parashar, Erhan Gundogdu, Mathieu Salzmann, Pascal Fua

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations.