一键生成可动画3D角色,1秒内完成任意形态绑定
Make-It-Animatable: An Efficient Framework for Authoring Animation-Ready 3D Characters
- 用粒子自编码器统一处理网格与3D高斯点云
- 1秒内生成高质量权重、骨骼和姿态变换
- 支持非标准骨架,适合创意设计与游戏开发
3D角色在现代创意产业中至关重要,但使其可动画化通常需要大量手动工作,如绑定和蒙皮。现有自动绑定工具存在依赖人工标注、骨架拓扑僵硬、跨形状泛化能力差等问题。另一种方法是生成预绑定到模板网格的可动画化身,但灵活性不足,且多局限于真实人体。为此,我们提出Make-It-Animatable,一种新型数据驱动方法,可在不到1秒内使任意3D类人模型具备动画能力,无论其形态与姿态如何。该统一框架生成高质量的混合权重、骨骼及姿态变换。通过引入基于粒子的形状自编码器,方法支持多种3D表示形式,包括网格与3D高斯点云。同时采用粗到细表示与结构感知建模策略,确保在非标准骨架下仍具准确性和鲁棒性。我们进行了广泛实验验证框架有效性。相比现有方法,本方案在质量和速度上均有显著提升。更多演示与代码见https://jasongzy.github.io/Make-It-Animatable/
原文摘要 · Abstract (English)
3D characters are essential to modern creative industries, but making them animatable often demands extensive manual work in tasks like rigging and skinning. Existing automatic rigging tools face several limitations, including the necessity for manual annotations, rigid skeleton topologies, and limited generalization across diverse shapes and poses. An alternative approach is to generate animatable avatars pre-bound to a rigged template mesh. However, this method often lacks flexibility and is typically limited to realistic human shapes. To address these issues, we present Make-It-Animatable, a novel data-driven method to make any 3D humanoid model ready for character animation in less than one second, regardless of its shapes and poses. Our unified framework generates high-quality blend weights, bones, and pose transformations. By incorporating a particle-based shape autoencoder, our approach supports various 3D representations, including meshes and 3D Gaussian splats. Additionally, we employ a coarse-to-fine representation and a structure-aware modeling strategy to ensure both accuracy and robustness, even for characters with non-standard skeleton structures. We conducted extensive experiments to validate our framework's effectiveness. Compared to existing methods, our approach demonstrates significant improvements in both quality and speed. More demos and code are available at https://jasongzy.github.io/Make-It-Animatable/.
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