paper-with-me

홈 › Papers

HMC: Hierarchical Mesh Coarsening for Skeleton-free Motion Retargeting

2023-03-20 · Haoyu Wang, Shaoli Huang, Fang Zhao, Chun Yuan, Ying Shan

We present a simple yet effective method for skeleton-free motion retargeting. Previous methods transfer motion between high-resolution meshes, failing to preserve the inherent local-part motions in the mesh. Addressing this issue, our proposed method learns the correspondence in a coarse-to-fine fashion by integrating the retargeting process with a mesh-coarsening pipeline. First, we propose a mesh-coarsening module that coarsens the mesh representations for better motion transfer. This module improves the ability to handle small-part motion and preserves the local motion interdependence between neighboring mesh vertices. Furthermore, we leverage a hierarchical refinement procedure to complement missing mesh details by gradually improving the low-resolution mesh output with a higher-resolution one. We evaluate our method on several well-known 3D character datasets, and it yields an average improvement of 25% on point-wise mesh euclidean distance (PMD) against the start-of-art method. Moreover, our qualitative results show that our method is significantly helpful in preserving the moving consistency of different body parts on the target character due to disentangling body-part structures and mesh details in a hierarchical way.

📄 PDF Abstract BibTeX arXiv:2303.10941

Code (0)

등록된 구현이 없습니다.

Tasks

motion retargeting

Similar Papers 제목 키워드 기반

STMT: A Spatial-Temporal Mesh Transformer for MoCap-Based Action Recognition

2023-03-31 · CVPR 2023 1 · Xiaoyu Zhu, Po-Yao Huang, Junwei Liang, Celso M. de Melo 외

We study the problem of human action recognition using motion capture (MoCap) sequences. Unlike existing techniques that take multiple manual steps to derive standardized skeleton representations as model input, we propo…

Action RecognitionTemporal Action Localization

Skeleton2Stage: Reward-Guided Fine-Tuning for Physically Plausible Dance Generation

2026-02-14 · Jidong Jia, Youjian Zhang, Huan Fu, Dacheng Tao arxiv

Despite advances in dance generation, most methods are trained in the skeletal domain and ignore mesh-level physical constraints. As a result, motions that look plausible as joint trajectories often exhibit body self-pen…

Reinforcement LearningMotion Synthesis

TapMo: Shape-aware Motion Generation of Skeleton-free Characters

2023-10-19 · Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen 외

Previous motion generation methods are limited to the pre-rigged 3D human model, hindering their applications in the animation of various non-rigged characters. In this work, we present TapMo, a Text-driven Animation Pip…

Motion Generation

SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation

2026-07-09 · Hao Feng, Zhi Zuo, Jia-Hui Pan, Ka-Hei Hui 외 arxiv

We study 4D generation to synthesize temporally coherent sequences of 3D geometry for animation and content creation. In contrast to existing SDS-based optimization methods and video-driven animation approaches, we adopt…

ASMR: Adaptive Skeleton-Mesh Rigging and Skinning via 2D Generative Prior

2025-03-17 · Seokhyeon Hong, Soojin Choi, Chaelin Kim, Sihun Cha 외

Despite the growing accessibility of skeletal motion data, integrating it for animating character meshes remains challenging due to diverse configurations of both skeletons and meshes. Specifically, the body scale and bo…