arXiv Computer Vision By Yajing Chen, Xin Chen, Saidan Lu, Yeqi Yuan, Weikai Chen, Changyu Hu, Cheng Zeng, Xin Wang

TailorRig: Controllable and Structured Auxiliary Skeleton Generation for Garment-Aware Rigging

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Hugging Face Trending Papers
Jul 30

ViP-Rig: Visual-Prompted Controllable Rigging

Rigging is inherently task-dependent because the same mesh may require different skeletons and deformation behaviors across animation tasks. In practice, artists often inspect an initial rig and repeatedly edit its skeletal structure and deformation behavior to meet specific animation requirements.

arXiv AI
Oct 15

Inverse Garment Design with Visual Agents

arXiv:2610.15582v1 Announce Type: new Abstract: We study the problem of inverse garment design, reconstructing simulation-ready 3D outfits with arbitrary layers from a single image, with visual agent...

By Nanxiang Jiang, Yunuo Chen, Zeng Tao, Zizhang Li, Qi Guo, Jiajun Wu, Yin Yang, Chenfanfu Jiang
arXiv Computer Vision
Sep 3

Make-It-Poseable: Feed-forward Latent Posing Model for 3D Characters

Make‑It‑Poseable is a feed‑forward framework that treats 3D character posing as a skinning‑free latent‑space transformation. It decouples shape deformation from fixed mesh connectivity, using a latent posing transformer, dense pose representation, and an adaptive completion module with bipartite‑matched latent loss. Experiments show it outperforms existing baselines, generalizes to varied morphologies, and supports 3D authoring tasks such as part replacement and refinement.

By Zhiyang Guo, Ori Zhang, Jax Xiang, Alan Zhao, Zhenxun Yuan, Wengang Zhou, Houqiang Li
Hugging Face Trending Papers
Oct 29

RFW-A: Agentic Procedural Generation of 400K Articulated Assets over 500 Categories

RFW‑A introduces a hybrid approach that combines agentic synthesis with procedural generation to create reusable category‑level generators for articulated assets. By testing and refining these generators across sampled configurations, the system can produce over 400 K high‑quality, simulation‑ready assets across 500+ categories at a fraction of the cost per asset. The resulting dataset demonstrates strong structural validity, robust physics simulation, and improves downstream tasks such as part‑level articulation estimation and zero‑shot policy transfer to real objects.

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