OmniFabric is a new method for creating production‑ready 3D garment assets from a single image. It generates globally coherent texture maps directly in the 2D sewing pattern (UV) space, using a coarse initialization from Vision‑Language Models and refining it with a diffusion transformer conditioned on 3D positional features. The approach removes distortion and baked‑in artifacts, producing photorealistic 3D garments with high‑quality textures that outperform current state‑of‑the‑art baselines.
By Ding-Jiun Huang, Yuanhao Wang, Cheng Zhang, Hugo Bertiche, Alexandru-Eugen Ichim, Thabo Beeler, Fernando De la Torre
OmniFabric is a new method for creating high‑quality, globally coherent texture maps for 3D garment reconstruction from a single image. It first generates a coarse texture initialization on the garment’s sewing pattern using a 3D mesh and Vision‑Language Model priors, then refines this in the UV domain with a diffusion transformer conditioned on 3D positional features. The approach removes distortion and baked‑in artifacts, producing photorealistic 3D garments that outperform existing baselines.
arXiv:2602.24043v2 Announce Type: replace
Abstract: Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, an...
By Yingxuan You, Ren Li, Corentin Dumery, Cong Cao, Hao Li, Pascal Fua
arXiv:2609.09513v1 Announce Type: new
Abstract: Reconstructing a fully animatable 3D animal from a single image remains challenging because animation-ready assets require not only plausible geometry,...
By Chunyi Sun, Ruyi Zha, Weijian Deng, Junlin Han, Dylan Campbell, Stephen Gould
arXiv:2607. 23189v1 Announce Type: cross Abstract: AI-generated content (AIGC) has made significant progress, with 2D generative models becoming ready-to-use tools for the digital fashion industry.
By Shenghao Yang, Hongtao Zhang, Yuhan Yi, Zhihao Tang, Zihao Cui, Lian Wen, Han Yan, Yuan Gao, Mingbo Zhao
The paper introduces AvaImg, a multi‑stage optimization pipeline that achieves high‑fidelity SMPL(-X)+D registrations with UV texture for arbitrary clothed scans. By enforcing a body‑inside‑clothing constraint through signed winding numbers and employing a three‑level efficiency cascade, AvaImg significantly reduces runtime and storage while recovering fine surface detail via coarse‑to‑fine displacement optimization. The resulting textured registrations are nearly indistinguishable from scans, and encoding the UV maps with a frozen FLUX VAE demonstrates compatibility with 2D generative models, enabling 3D avatar generation using image‑based priors.
By Margaret Kostyrko, Yuxuan Xue, Garvita Tiwari, Gerard Pons-Moll
arXiv:2608.25461v1 Announce Type: cross
Abstract: Using conditional image generators, texture artists can explore many single-view looks for an existing 3D shape. Despite impressive progress, state-o...
By Chenyue Cai, Anita Hu, James Lucas, Szymon Rusinkiewicz, Masha Shugrina
arXiv:2608. 19900v1 Announce Type: new Abstract: For full-body avatars, modeling surface dynamics is crucial for overcoming the uncanny valley and achieving perceptual realism.
By Guoxing Sun, Heming Zhu, Linjie Lyu, Pascal Fua, Christian Theobalt, Marc Habermann
arXiv:2609.18510v1 Announce Type: new
Abstract: We present DiT-Garment to model dynamic 3D clothing over human body models in arbitrary motion. Unlike existing methods, DiT-Garment can animate garmen...
By Antoine Dumoulin, Laurence Boissieux, Joao Regateiro, Pierre Hellier, Stefanie Wuhrer
arXiv:2606. 27923v1 Announce Type: cross Abstract: We present Home3D 1.
By Yiyun Fei, Guoqiu Li, Jin Song, Chuqiao Wu, Delong Wu, Hong Wu, Ziru Zeng, Haohui Chen, YinDong Kong, Jing Li, Qi Wu, Feng Zhang
The paper introduces HyperBones, a real‑time garment simulation framework that combines a reduced‑space neural dynamics simulator with a lightweight neural network correcting Linear Blend Skinning (LBS) at a coarse level, and a convolutional MLP for fine‑scale wrinkle recovery in UV space. By decoupling identity‑specific computation from shape conditioning through a hypernetwork, the method achieves high performance without an offline simulator, delivering physically plausible dynamics across diverse motions and unseen body shapes. Experiments demonstrate a speedup of over 30× compared to state‑of‑the‑art autoregressive neural simulators, reaching interactive inference at roughly 1 ms per frame on a consumer GPU.
By Astitva Srivastava, Hsiao-Yu Chen, Ryan Goldade, Philipp Herholz, Zhongshi Jiang, Gene Wei-Chin Lin, Lingchen Yang, Nikolaos Sarafianos, Tuur Stuyck, Avinash Sharma, Egor Larionov
arXiv:2511. 16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image.
By SAM 3D Team, Xingyu Chen, Fu-Jen Chu, Pierre Gleize, Kevin J Liang, Alexander Sax, Hao Tang, Weiyao Wang, Michelle Guo, Thibaut Hardin, Xiang Li, Aohan Lin, Jiawei Liu, Ziqi Ma, Anushka Sagar, Bowen Song, Xiaodong Wang, Jianing Yang, Bowen Zhang, Piotr Doll\'ar, Georgia Gkioxari, Matt Feiszli, Jitendra Malik