AI RESEARCH
Zero-Shot Reconstruction of Animatable 3D Avatars with Cloth Dynamics from a Single Image
arXiv CS.CV
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ArXi:2603.14772v1 Announce Type: new Existing single-image 3D human avatar methods primarily rely on rigid joint transformations, limiting their ability to model realistic cloth dynamics. We present DynaAvatar, a zero-shot framework that reconstructs animatable 3D human avatars with motion-dependent cloth dynamics from a single image. Trained on large-scale multi-person motion datasets, DynaAvatar employs a Transformer-based feed-forward architecture that directly predicts dynamic 3D Gaussian deformations without subject-specific optimization. To overcome the scarcity of dynamic captures, we.