AI RESEARCH
MotionDreamer: Universal Skeletal Motion Generation for 3D Rigged Shapes
arXiv CS.CV
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ArXi:2606.01518v1 Announce Type: new Motion generation for rigged shapes is vital for scalable 4D asset production. However, template-based methods are limited by specific topologies and fail to generalize across diverse morphologies. Conversely, per-case optimization is computationally expensive, susceptible to local optima, and highly sensitive to viewpoint-induced ambiguities. In this paper, we present MotionDreamer, a diffusion-based framework designed for category-agnostic skeletal animation generation from 2D video guidance. To overcome the scarcity of high-quality