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arXiv cs.GR
arXiv cs.GR Research
· 4 months, 3 weeks ago • Mingze Sun, Cheng Zeng, Jiansong Pei, Junhao Chen, Chaoyue Song, Shaohui Wang, Tianyuan Chang, Bin Huang, Zijiao Zeng, Ruqi Huang

Animator-Centric Skeleton Generation on Objects with Fine-Grained Details

Briefing

The proposed framework introduces a novel semantic-aware tokenization scheme that enhances the robustness of skeleton generation for complex models. This is particularly beneficial for animators, as it allows for soft control over bone density, addressing a critical bottleneck in animation workflows. The large-scale dataset of 82,633 rigged meshes provides a solid foundation for training, ensuring high-quality outputs even for intricate designs.

For developers, this advancement means less time spent on manual rigging and more focus on creative aspects of animation. As the demand for detailed 3D assets grows, tools that streamline the animation process will become increasingly valuable, making this framework a noteworthy development in the field of graphics programming.

“Our framework not only generates high-quality skeletons but also fulfills critical requirements from professional animators.”

— Mingze Sun · Discussing the framework's capabilities
Original source
Read on arXiv cs.GR
At a glance
what
Introduction of an animator-centric skeleton generation framework
who
Authors: Mingze Sun, Cheng Zeng, and 9 others
when
Submitted on 22 Apr 2026
impact
Improves animation workflows for 3D asset creation
Signal Positive

This framework significantly enhances animation efficiency and quality.

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