Search Results for author: Tuur Stuyck

Found 8 papers, 0 papers with code

Garment3DGen: 3D Garment Stylization and Texture Generation

no code implementations27 Mar 2024 Nikolaos Sarafianos, Tuur Stuyck, Xiaoyu Xiang, Yilei Li, Jovan Popovic, Rakesh Ranjan

We present a plethora of quantitative and qualitative comparisons on various assets both real and generated and provide use-cases of how one can generate simulation-ready 3D garments.

DiffAvatar: Simulation-Ready Garment Optimization with Differentiable Simulation

no code implementations20 Nov 2023 Yifei Li, Hsiao-yu Chen, Egor Larionov, Nikolaos Sarafianos, Wojciech Matusik, Tuur Stuyck

The realism of digital avatars is crucial in enabling telepresence applications with self-expression and customization.

Physical Simulations

PhysGraph: Physics-Based Integration Using Graph Neural Networks

no code implementations27 Jan 2023 Oshri Halimi, Egor Larionov, Zohar Barzelay, Philipp Herholz, Tuur Stuyck

Our contribution is based on a simple observation: evaluating forces is computationally relatively cheap for traditional simulation methods and can be computed in parallel in contrast to their integration.

Virtual Try-on

Dressing Avatars: Deep Photorealistic Appearance for Physically Simulated Clothing

no code implementations30 Jun 2022 Donglai Xiang, Timur Bagautdinov, Tuur Stuyck, Fabian Prada, Javier Romero, Weipeng Xu, Shunsuke Saito, Jingfan Guo, Breannan Smith, Takaaki Shiratori, Yaser Sheikh, Jessica Hodgins, Chenglei Wu

The key idea is to introduce a neural clothing appearance model that operates on top of explicit geometry: at training time we use high-fidelity tracking, whereas at animation time we rely on physically simulated geometry.

Virtual Elastic Objects

no code implementations CVPR 2022 Hsiao-yu Chen, Edgar Tretschk, Tuur Stuyck, Petr Kadlecek, Ladislav Kavan, Etienne Vouga, Christoph Lassner

We present Virtual Elastic Objects (VEOs): virtual objects that not only look like their real-world counterparts but also behave like them, even when subject to novel interactions.

HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capture

no code implementations CVPR 2022 Ziyan Wang, Giljoo Nam, Tuur Stuyck, Stephen Lombardi, Michael Zollhoefer, Jessica Hodgins, Christoph Lassner

Capturing and rendering life-like hair is particularly challenging due to its fine geometric structure, the complex physical interaction and its non-trivial visual appearance. Yet, hair is a critical component for believable avatars.

Neural Rendering Optical Flow Estimation

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