Hugging Face Trending Papers
Sep 24

OmniFabric: Coherent UV Space Texture Synthesis for 3D Garment Reconstruction

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 Computer Vision
Sep 25

OmniFabric: Coherent UV Space Texture Synthesis for 3D Garment Reconstruction

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
arXiv Computer Vision
Sep 7

HyperBones: Realtime Bone-driven Neural Garment Simulation with Hypernetwork Conditioning

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 AI
Sep 1

GarmentWeaver: Schema-Aware Structured Synthesis for Multimodal Sewing Patterns

GarmentWeaver is a new framework for multimodal sewing pattern generation that uses a schema‑aware approach to construct compact hierarchical targets. By activating garment‑relevant structural branches and building on a pretrained vision‑language model, it predicts executable sewing patterns in a structured manner. Experiments show that GarmentWeaver produces more accurate, executable patterns and yields better simulation results than strong baselines.

By Yinwen Lu, Weihao Luo, Yueqi Zhong