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SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing [article]

Garvita Tiwari, Bharat Lal Bhatnagar, Tony Tung, Gerard Pons-Moll
2020 arXiv   pre-print
in a single pass from an input mesh.  ...  In this paper, we introduce SizerNet to predict 3D clothing conditioned on human body shape and garment size parameters, and ParserNet to infer garment meshes and shape under clothing with personal details  ...  This work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -409792180 (Emmy Noether Programme, project: Real Virtual Humans) and a Facebook research award.  ... 
arXiv:2007.11610v1 fatcat:3xgsldepmzbpfbqsuvxt2suzbq

Detailed, accurate, human shape estimation from clothed 3D scan sequences [article]

Chao Zhang, Sergi Pujades, Michael Black, Gerard Pons-Moll
2017 arXiv   pre-print
Scanning bodies in minimal clothing, however, presents a practical barrier to these applications. We address this problem by estimating body shape under clothing from a sequence of 3D scans.  ...  We address the problem of estimating human pose and body shape from 3D scans over time.  ...  Acknowledgments We thank the authors of [21] and [44] for providing their results for comparison. We especially thank the authors of [45] for running their method on BUFF.  ... 
arXiv:1703.04454v2 fatcat:mhkfc7cig5amzenv5ulmyycz4u

Detailed, Accurate, Human Shape Estimation from Clothed 3D Scan Sequences

Chao Zhang, Sergi Pujades, Michael Black, Gerard Pons-Moll
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We show several pairs of clothed scan sequences and the estimated body shape underneath.  ...  Figure 1 : Given static 3D scans or 3D scan sequences (in pink), we estimate the naked shape under clothing (beige).  ...  Acknowledgments We thank the authors of [21] and [44] for providing their results for comparison. We especially thank the authors of [45] for running their method on BUFF.  ... 
doi:10.1109/cvpr.2017.582 dblp:conf/cvpr/ZhangPBP17 fatcat:w56qgfc4zjc3bgzsmyoq6tub34

Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction [article]

Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, Gerard Pons-Moll
2021 arXiv   pre-print
We subsequently use correspondences to fit the body model to our inner surface and then non-rigidly deform it (under a parametric body + displacement model) to the outer surface in order to capture garment  ...  , and the semantic correspondences to a parametric body model.  ...  Some work have focused on estimating body shape under clothing [61,10,55], or capturing body shape and clothing jointly from scans [35].  ... 
arXiv:2007.11432v2 fatcat:mtcxrvdszjc4fhfo7gztc74gqq

TightCap: 3D Human Shape Capture with Clothing Tightness Field [article]

Xin Chen, Anqi Pang, Yang Wei, Lan Xui, Jingyi Yu
2021 arXiv   pre-print
In this paper, we present TightCap, a data-driven scheme to capture both the human shape and dressed garments accurately with only a single 3D human scan, which enables numerous applications such as virtual  ...  To break the severe variations of the human poses and garments, we propose to model the clothing tightness - the displacements from the garments to the human shape implicitly in the global UV texturing  ...  ACKNOWLEDGMENTS The authors would like to thank WenGuang Ma, YeCheng Qiu, MingGuang Chen for help with data acquisition; Hongbo Wang, Gao Ya, Shenze Ye, Teng Su for help with data annotation.  ... 
arXiv:1904.02601v4 fatcat:qez4hn3g25afxn5kvrqejsivxe

Estimation of human body shape and posture under clothing

Stefanie Wuhrer, Leonid Pishchulin, Alan Brunton, Chang Shu, Jochen Lang
2014 Computer Vision and Image Understanding  
In case of motion sequences, our method takes advantage of motion cues to solve for a single body shape estimate along with a sequence of posture estimates.  ...  Our method can estimate the body shape and posture of both static scans and motion sequences of dressed human body scans.  ...  scanning experiment.  ... 
doi:10.1016/j.cviu.2014.06.012 fatcat:n65ixobqtzbhnnt3jt3bcjpqjm

Multi-Garment Net: Learning to Dress 3D People From Images

Bharat Bhatnagar, Garvita Tiwari, Christian Theobalt, Gerard Pons-Moll
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL [40] model from a few frames (1-8) of a video.  ...  Garments from the digital wardrobe, or predicted by MGN, can be used to dress any body shape in arbitrary poses.  ...  We thank twindom ( for providing scan data, Thiemo Alldieck for providing code for texture/segmentation stitching, and Verica Lazova for discussions.  ... 
doi:10.1109/iccv.2019.00552 dblp:conf/iccv/BhatnagarTTP19 fatcat:4nkadzerfrgk3cao3bilwnjkba


Gerard Pons-Moll, Sergi Pujades, Sonny Hu, Michael J. Black
2017 ACM Transactions on Graphics  
From left to right: (1) An example 3D textured scan that is part of a 4D sequence. (2) Our multi-part aligned mesh model, layered over the body. (3) The estimated minimally clothed shape (MCS) under the  ...  Note that the clothing adapts in a natural way to the new body shape. (5) This new body shape posed in a new, never seen, pose.  ...  Zaman for help with video editing and voice recording; A. Quiros Ramirez for help with the project website.  ... 
doi:10.1145/3072959.3073711 fatcat:qjvyyjgy6vcb3kh26xzpd3aksm

The Naked Truth: Estimating Body Shape Under Clothing [chapter]

Alexandru O. Bălan, Michael J. Black
2008 Lecture Notes in Computer Science  
The approach exploits a model of human body shapes that is learned from a database of over 2000 range scans.  ...  We propose a method to estimate the detailed 3D shape of a person from images of that person wearing clothing.  ...  This work was supported in part by the Office of Naval Research (N00014-07-1-0803), NSF (IIS-0535075), by an award from the Rhode Island Economic Development Corporation (STAC), and by a gift from Intel  ... 
doi:10.1007/978-3-540-88688-4_2 fatcat:khb2xeduxzgh7f74gi6bvaaybe

Video Based Reconstruction of 3D People Models

Thiemo Alldieck, Marcus Magnor, Weipeng Xu, Christian Theobalt, Gerard Pons-Moll
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
Figure 1 : Our technique allows to extract for the first time accurate 3D human body models, including hair and clothing, from a single video sequence of the person moving in front of the camera such that  ...  Based on a parametric body model, we present a robust processing pipeline to infer 3D model shapes including clothed people with 4.5mm reconstruction accuracy.  ...  Acknowledgments The authors gratefully acknowledge funding by the German Science Foundation from project DFG MA2555/12-1.  ... 
doi:10.1109/cvpr.2018.00875 dblp:conf/cvpr/AlldieckMXTP18 fatcat:o4kwdol2ojhunonfgsilkx573e

Video Based Reconstruction of 3D People Models [article]

Thiemo Alldieck, Marcus Magnor, Weipeng Xu, Christian Theobalt, Gerard Pons-Moll
2018 arXiv   pre-print
This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving.  ...  This enables efficient estimation of a consensus 3D shape, texture and implanted animation skeleton based on a large number of frames.  ...  Acknowledgments The authors gratefully acknowledge funding by the German Science Foundation from project DFG MA2555/12-1.  ... 
arXiv:1803.04758v3 fatcat:6jwhxkpxi5bmtpccgzhgkcdopa

Estimation of human body shape and cloth field in front of a kinect

Ming Zeng, Liujuan Cao, Huailin Dong, Kunhui Lin, Meihong Wang, Jing Tong
2015 Neurocomputing  
This paper describes an easy-to-use system to estimate the shape of a human body and his/her clothes. The system uses a Kinect to capture the human's RGB and depth information from different views.  ...  After the body estimation, the body shape is non-rigidly deformed to fit the dressed shape, so as to extract the cloth field of the dressed shape.  ...  Acknowledgments We would like to thank the reviewers for their valuable comments. This  ... 
doi:10.1016/j.neucom.2014.06.087 fatcat:ppouqqj4frh2jgixsoqoj627km

Human Body Shape Estimation Using a Multi-resolution Manifold Forest

Frank Perbet, Sam Johnson, Minh-Tri Pham, Bjorn Stenger
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
This paper proposes a method for estimating the 3D body shape of a person with robustness to clothing.  ...  We formulate the problem as optimization over the manifold of valid depth maps of body shapes learned from synthetic training data.  ...  Human body shape estimation under clothing Given a noisy, incomplete depth sensor input of a clothed person we estimate their body shape by learning a manifold of depth maps rendered from unclothed human  ... 
doi:10.1109/cvpr.2014.91 dblp:conf/cvpr/PerbetJPS14 fatcat:aqhdrxggiradzpfhlmww7ou4bm

A 2D Human Body Model Dressed in Eigen Clothing [chapter]

Peng Guan, Oren Freifeld, Michael J. Black
2010 Lecture Notes in Computer Science  
The naked body is represented as a Contour Person that can take on a wide variety of poses and body shapes. Clothing is represented as a deformation from the underlying body contour.  ...  The resulting generative model captures realistic human forms in monocular images and is used to infer 2D body shape and pose under clothing.  ...  Reiss for generating the synthetic training data, A. Bȃlan for assistance with the real dataset, and S. Zuffi for helpful comments.  ... 
doi:10.1007/978-3-642-15549-9_21 fatcat:mgszsg7ewbb3xhn7lufs237the

DeepProfile: Accurate Under-the-Clothes Body Profile Estimation

Shufang Lu, Funan Lu, Xufeng Shou, Shuaiyin Zhu
2022 Applied Sciences  
a body profile database to generate under-the-clothes profiles.  ...  In this paper, we created and labeled an under-the-clothes human body contour keypoint dataset; we utilized a convolutional neural network (CNN) to extract the contour keypoints, then combined them with  ...  Data Availability Statement: To be supplied upon request. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12042220 fatcat:6iroqgdr2nemvjudwd3kz52hie
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