Zobrazeno 1 - 10
of 76
pro vyhledávání: '"LIN, SIYOU"'
Estimating consistently oriented normals for point clouds enables a number of important applications in computer graphics. While local normal estimation is possible with simple techniques like PCA, orienting them to be globally consistent has been a
Externí odkaz:
http://arxiv.org/abs/2405.16634
Animatable clothing transfer, aiming at dressing and animating garments across characters, is a challenging problem. Most human avatar works entangle the representations of the human body and clothing together, which leads to difficulties for virtual
Externí odkaz:
http://arxiv.org/abs/2405.07319
We address the problem of aligning real-world 3D data of garments, which benefits many applications such as texture learning, physical parameter estimation, generative modeling of garments, etc. Existing extrinsic methods typically perform non-rigid
Externí odkaz:
http://arxiv.org/abs/2308.09519
Autor:
Su, Zhaoqi, Hu, Liangxiao, Lin, Siyou, Zhang, Hongwen, Zhang, Shengping, Thies, Justus, Liu, Yebin
We present CaPhy, a novel method for reconstructing animatable human avatars with realistic dynamic properties for clothing. Specifically, we aim for capturing the geometric and physical properties of the clothing from real observations. This allows
Externí odkaz:
http://arxiv.org/abs/2308.05925
Autor:
Zhang, Hongwen, Lin, Siyou, Shao, Ruizhi, Zhang, Yuxiang, Zheng, Zerong, Huang, Han, Guo, Yandong, Liu, Yebin
Creating animatable avatars from static scans requires the modeling of clothing deformations in different poses. Existing learning-based methods typically add pose-dependent deformations upon a minimally-clothed mesh template or a learned implicit te
Externí odkaz:
http://arxiv.org/abs/2304.03167
We present FITE, a First-Implicit-Then-Explicit framework for modeling human avatars in clothing. Our framework first learns implicit surface templates representing the coarse clothing topology, and then employs the templates to guide the generation
Externí odkaz:
http://arxiv.org/abs/2207.06955
Surface reconstruction is a fundamental problem in 3D graphics. In this paper, we propose a learning-based approach for implicit surface reconstruction from raw point clouds without normals. Our method is inspired by Gauss Lemma in potential energy t
Externí odkaz:
http://arxiv.org/abs/2111.09526
Autor:
Zhao, Xiaochen, Zheng, Zerong, Ji, Chaonan, Liu, Zhenyi, Lin, Siyou, Yu, Tao, Suo, Jinli, Liu, Yebin
We introduce VERTEX, an effective solution to recover 3D shape and intrinsic texture of vehicles from uncalibrated monocular input in real-world street environments. To fully utilize the template prior of vehicles, we propose a novel geometry and tex
Externí odkaz:
http://arxiv.org/abs/2011.14642
Publikováno v:
In Computers & Graphics February 2022 102:309-319
Akademický článek
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