可驱动姿态生成：面向三维人形角色动画的前馈式潜在姿态建模

摘要

三维角色姿态设定是计算机图形学与视觉领域的基础任务。然而现有方法如自动骨骼绑定和姿态条件生成常面临蒙皮权重预测不准、拓扑结构缺陷及姿态贴合度差等挑战，制约了其鲁棒性与泛化能力。为突破这些局限，我们提出Make-It-Poseable这一创新前馈框架，将角色姿态设定重新定义为隐空间变换问题。与传统流程中变形网格顶点不同，我们的方法通过直接操控隐表征来重建新姿态下的角色。其核心是基于骨骼运动操控形状标记的隐空间姿态变换器，辅以密集姿态表征实现精准控制。为确保高保真几何并适应拓扑变化，我们还引入了隐空间监督策略与自适应补全模块。本方法在姿态质量上展现出卓越性能，并能自然扩展到部件替换与精细化等三维编辑应用。

English

Posing 3D characters is a fundamental task in computer graphics and vision. However, existing methods like auto-rigging and pose-conditioned generation often struggle with challenges such as inaccurate skinning weight prediction, topological imperfections, and poor pose conformance, limiting their robustness and generalizability. To overcome these limitations, we introduce Make-It-Poseable, a novel feed-forward framework that reformulates character posing as a latent-space transformation problem. Instead of deforming mesh vertices as in traditional pipelines, our method reconstructs the character in new poses by directly manipulating its latent representation. At the core of our method is a latent posing transformer that manipulates shape tokens based on skeletal motion. This process is facilitated by a dense pose representation for precise control. To ensure high-fidelity geometry and accommodate topological changes, we also introduce a latent-space supervision strategy and an adaptive completion module. Our method demonstrates superior performance in posing quality. It also naturally extends to 3D editing applications like part replacement and refinement.

可驱动姿态生成：面向三维人形角色动画的前馈式潜在姿态建模

Make-It-Poseable: Feed-forward Latent Posing Model for 3D Humanoid Character Animation

摘要

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