171 citations · 219 across the 4 of their papers we have counts for
6 papers
SNUG: Self-Supervised Neural Dynamic Garments
Igor Santesteban, Miguel A. Otaduy, Dan Casas
We present a self-supervised method to learn dynamic 3D deformations of garments worn by parametric human bodies. State-of-the-art data-driven approaches to model 3D garment deform…
RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video
Jiayi Wang, Franziska Mueller, Florian Bernard +6
Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a challenging problem that has a high relevance for several human-computer interaction applicati…
Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera
Franziska Mueller, Micah Davis, Florian Bernard +5
We present a novel method for real-time pose and shape reconstruction of two strongly interacting hands. Our approach is the first two-hand tracking solution that combines an exten…
Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On
Igor Santesteban, Nils Thuerey, Miguel A. Otaduy +1
We propose a new generative model for 3D garment deformations that enables us to learn, for the first time, a data-driven method for virtual try-on that effectively addresses garme…
SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans
Igor Santesteban, Elena Garces, Miguel A. Otaduy +1
We present SoftSMPL, a learning-based method to model realistic soft-tissue dynamics as a function of body shape and motion. Datasets to learn such task are scarce and expensive to…
Learning-Based Animation of Clothing for Virtual Try-On
Igor Santesteban, Miguel A. Otaduy, Dan Casas
This paper presents a learning-based clothing animation method for highly efficient virtual try-on simulation. Given a garment, we preprocess a rich database of physically-based dr…