Efficient simulation of inextensible cloth

GoldenthalRony,; HarmonDavid,; FattalRaanan,; Bercovier, Michel; GrinspunEitan,

doi:10.1145/1276377.1276438

Cited by 195 publications

(71 citation statements)

References 23 publications

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“…external forces have to be taken into account such as body kinematics, body surface friction, interpenetration, etc [9,8,4,16]. Note that several models have been integrated in commercial solutions (e.g., Unreal Engine APEX Cloth/Nvidia NvCloth, Unity Cloth, Maya nCloth, MarvelousDesigner, OptiTex, etc.)…”

Section: Related Workmentioning

confidence: 99%

DeepWrinkles: Accurate and Realistic Clothing Modeling

Lähner

Cremers

Tung

2018

Lecture Notes in Computer Science

189

176

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We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physicsbased simulation (with numerous heuristic parameters), while models reconstructed from visual observations typically suffer from lack of geometric details. Here, we propose an original framework consisting of two modules that work jointly to represent global shape deformation as well as surface details with high fidelity. Global shape deformations are recovered from a subspace model learned from 3D data of clothed people in motion, while high frequency details are added to normal maps created using a conditional Generative Adversarial Network whose architecture is designed to enforce realism and temporal consistency. This leads to unprecedented high-quality rendering of clothing deformation sequences, where fine wrinkles from (real) high resolution observations can be recovered. In addition, as the model is learned independently from body shape and pose, the framework is suitable for applications that require retargeting (e.g., body animation). Our experiments show original high quality results with a flexible model. We claim an entirely data-driven approach to realistic cloth wrinkle generation is possible.

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Section: Related Workmentioning

confidence: 99%

DeepWrinkles: Accurate and Realistic Clothing Modeling

Lähner

Cremers

Tung

2018

Lecture Notes in Computer Science

189

176

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“…3D clothing models. Much of the work in the field of clothing modeling is focused on how to make simulation faster [9,30], particularly by adding realistic wrinkles to low-resolution simulations [20,22]. Other approaches have focused on taking off-line simulations and learning data driven models from them [7,13,22,44,49].…”

Section: D Models Of People In Clothingmentioning

confidence: 99%

A Generative Model of People in Clothing

Lassner

Pons-Moll

Gehler

2017

2017 IEEE International Conference on Computer Vision (ICCV)

230

206

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Figure 1: Random examples of people generated with our model. For each row, sampling is conditioned on the silhouette displayed on the left. Our proposed framework also supports unconditioned sampling as well as conditioning on local appearance cues, such as color. AbstractWe present the first image-based generative model of people in clothing for the full body. We sidestep the commonly used complex graphics rendering pipeline and the need for high-quality 3D scans of dressed people. Instead, we learn generative models from a large image database. The main challenge is to cope with the high variance in human pose, shape and appearance. For this reason, pure image-based approaches have not been considered so far. We show that this challenge can be overcome by splitting the generating process in two parts. First, we learn to generate a semantic segmentation of the body and clothing. Second, we learn a conditional model on the resulting segments that creates realistic images. The full model is differentiable and can be conditioned on pose, shape or color. The result are samples of people in different clothing items and styles. The proposed model can generate entirely new people with realistic clothing. In several experiments we present encouraging results that suggest an entirely data-driven approach to people generation is possible. * This work was performed while P. V. Gehler was with the BCCN 1 and MPI-IS 2 .

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“…Several approximations have been proposed, from simple spring-mass systems able to capture stretching and bending modes at first order, to Discrete Rod Models 47 that accurately capture dynamics in three-dimensional space, accounting for various modes of deformation. The graphics community has been most active in this area, where the use of Cosserat model 48 and its (far more popular) unstretchable and unshearable counterpart, the Kirchoff model 49 , have led to realistic simulations of elastic ribbons 50,51 , woven cloth 52,53 (Fig. 6d), entangled hair and fibers 51,54 (Fig.…”

Section: Materials Design and Role Of Simulationsmentioning

confidence: 99%

Mechanics of randomly packed filaments—The “bird nest” as meta-material

Weiner

Bhosale

Gazzola

et al. 2020

Journal of Applied Physics

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Systems of randomly packed, macroscopic elements, from jammed spherical grains to tangled long filaments, represent a broad class of disordered meta-materials with a wide range of applications and manifestations in nature. A 'bird nest' presents itself at an interface between hard round grains described by granular physics to long soft filaments, the center of textile material science. All of these randomly packed systems exhibit forms of self assembly, evident through their robust packing statistics, and a common, unusual elastoplastic response to oedometric compression. In reviewing packing statistics, mechanical response characterization and consideration of boundary effects, we present a perspective that attempts to establish a link between the bulk and local behaviour of a pile of sand and a wad of cotton, demonstrating the nest's relationship with each. Finally, potential directions for impactful applications are outlined.

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Efficient simulation of inextensible cloth

Cited by 195 publications

References 23 publications

DeepWrinkles: Accurate and Realistic Clothing Modeling

DeepWrinkles: Accurate and Realistic Clothing Modeling

A Generative Model of People in Clothing

Mechanics of randomly packed filaments—The “bird nest” as meta-material

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