用文本生成带骨骼的4D动画，无需逐帧标注。
SkelGen4D: Weakly-Supervised Skeleton-Based 4D Generation for Text-Driven Mesh Animation
- 通过可微拟合恢复伪骨骼，实现弱监督下的骨架生成。
- 在两个基准上优于或媲美全监督方法，支持多样物体类别。
- 适合需要可控编辑和工业流水线兼容的动画制作场景。
我们研究4D生成，旨在为动画与内容创作合成时序连贯的3D几何序列。不同于现有的基于SDS优化的方法和视频驱动的动画方式，我们采用符合标准工业流程的骨骼驱动动画框架，实现显式控制与编辑。为此，提出SkelGen4D：一种弱监督的前馈式文本驱动网格动画框架，可在无需逐帧骨骼标注的情况下生成显式骨架运动。SkelGen4D首先通过可微拟合从动画网格中恢复时序一致的伪骨骼，然后以前馈方式生成文本条件的骨架运动序列，并进一步通过Motion-GRPO优化，确保运动时序连贯、物理合理且具关节性。我们在两个大规模基准Truebones Zoo和Diffusion4D上评估该方法，结果表明，弱监督骨架建模达到或超越全监督基线，且能扩展至多样化物体类别，实现高质量文本驱动网格动画。此外，该方法支持灵活运动编辑，并与标准动画生产流程对齐。
原文摘要 · Abstract (English)
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 a skeleton-driven animation framework aligned with standard industrial pipelines, which enables explicit control and editing. To this end, we propose SkelGen4D, a weakly supervised feed-forward framework for text-driven mesh animation that generates explicit skeleton motions without requiring per-frame skeleton annotations. SkelGen4D first recovers temporally consistent pseudo-skeletons from animated meshes via differentiable fitting, and then generates text-conditioned skeleton motion sequences in a feed-forward manner, further refined with Motion-GRPO to ensure temporally coherent, physically plausible, and articulated animation. We evaluate our method on two large-scale benchmarks, Truebones Zoo and Diffusion4D. Our results show that our weakly supervised skeleton modeling matches or surpasses fully supervised baselines while scaling to diverse object categories for high-quality text-driven mesh animation. Further, our method supports flexible motion editing and is aligned with standard animation production pipelines.
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