14 citations · 32 across the 4 of their papers we have counts for
6 papers
HOOD: Hierarchical Graphs for Generalized Modelling of Clothing Dynamics
Artur Grigorev, Bernhard Thomaszewski, Michael J. Black +1
We propose a method that leverages graph neural networks, multi-level message passing, and unsupervised training to enable real-time prediction of realistic clothing dynamics. Wher…
Computational Design of Kinesthetic Garments
Velko Vechev, Juan Zarate, Bernhard Thomaszewski +1
Kinesthetic garments provide physical feedback on body posture and motion through tailored distributions of reinforced material. Their ability to selectively stiffen a garment's re…
SGN: Sparse Gauss-Newton for Accelerated Sensitivity Analysis
Jonas Zehnder, Stelian Coros, Bernhard Thomaszewski
We present a sparse Gauss-Newton solver for accelerated sensitivity analysis with applications to a wide range of equilibrium-constrained optimization problems. Dense Gauss-Newton…
NTopo: Mesh-free Topology Optimization using Implicit Neural Representations
Jonas Zehnder, Yue Li, Stelian Coros +1
Recent advances in implicit neural representations show great promise when it comes to generating numerical solutions to partial differential equations. Compared to conventional al…
Deep Physics-aware Inference of Cloth Deformation for Monocular Human Performance Capture
Yue Li, Marc Habermann, Bernhard Thomaszewski +3
Recent monocular human performance capture approaches have shown compelling dense tracking results of the full body from a single RGB camera. However, existing methods either do no…
ADD: Analytically Differentiable Dynamics for Multi-Body Systems with Frictional Contact
Moritz Geilinger, David Hahn, Jonas Zehnder +3
We present a differentiable dynamics solver that is able to handle frictional contact for rigid and deformable objects within a unified framework. Through a principled mollificatio…