Search Results for author:
Found 8 papers, 5 papers with code
Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images
We investigate the problem in the context of dressed humans under the wind.
Neural Cloth Simulation
Here, we propose the first methodology able to learn realistic cloth dynamics unsupervisedly, and henceforth, a general formulation for neural cloth simulation.
Neural Implicit Surfaces for Efficient and Accurate Collisions in Physically Based Simulations
Nonetheless, their memory footprint also grows rapidly and their parallelization in a GPU is problematic due to their branching nature.
Deep unsupervised 3D human body reconstruction from a sparse set of landmarks
In this paper we propose the first deep unsupervised approach in human body reconstruction to estimate body surface from a sparse set of landmarks, so called DeepMurf.
PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation
While deep-based approaches in the domain are becoming a trend, these are data-hungry models.
DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation
We present a novel solution to the garment animation problem through deep learning.
SMPLR: Deep SMPL reverse for 3D human pose and shape recovery
By implementing SMPLR as an encoder-decoder we avoid the need of complex constraints on pose and shape.
