SkeletonGaussian: Editable 4D Generation through Gaussian Skeletonization
4D generation has made remarkable progress in synthesizing dynamic 3D objects from input text, images, or videos. However, existing methods often represent motion as an implicit deformation field, which limits direct control and editability. To address this issue, we propose SkeletonGaussian, a novel framework for generating editable dynamic 3D Gaussians from monocular video input. Our approach introduces a hierarchical articulated representation that decomposes motion into sparse rigid motion explicitly driven by a skeleton and fine-grained non-rigid motion. Concretely, we extract a robust skeleton and drive rigid motion via linear blend skinning, followed by a hexplane-based refinement for non-rigid deformations, enhancing interpretability and editability. Experimental results demonstrate that SkeletonGaussian surpasses existing methods in generation quality while enabling intuitive motion editing, establishing a new paradigm for editable 4D generation. Project page: https://wusar.github.io/projects/skeletongaussian/
698489995de9acb9debfb219
Lifan Wu
698489995de9acb9debfb21a
Ruijie Zhu
claimed_verified
2026-02-06T18:53:01.990Z
6697ac8427e4e21a3a92da27
https://cdn-avatars.huggingface.co/v1/production/uploads/6697ac8427e4e21a3a92da27/9vn07-1_BBDk9zfDtDpcG.png
Ruijie Zhu
RuijieZhu
user
RuijieZhu
698489995de9acb9debfb21b
Yubo Ai
698489995de9acb9debfb21c
Tianzhu Zhang
SkeletonGaussian: Editable 4D Generation through Gaussian Skeletonization
4D generation has made remarkable progress in synthesizing dynamic 3D objects from input text, images, or videos. However, existing methods often represent motion as an implicit deformation field, which limits direct control and editability. To address this issue, we propose SkeletonGaussian, a novel framework for generating editable dynamic 3D Gaussians from monocular video input. Our approach introduces a hierarchical articulated representation that decomposes motion into sparse rigid motion explicitly driven by a skeleton and fine-grained non-rigid motion. Concretely, we extract a robust skeleton and drive rigid motion via linear blend skinning, followed by a hexplane-based refinement for non-rigid deformations, enhancing interpretability and editability. Experimental results demonstrate that SkeletonGaussian surpasses existing methods in generation quality while enabling intuitive motion editing, establishing a new paradigm for editable 4D generation. Project page: https://wusar.github.io/projects/skeletongaussian/
SkeletonGaussian enables editable 4D generation by decomposing motion into rigid skeleton-driven and non-rigid fine-grained components using hexplane-based refinement.
4D generation dynamic 3D objects monocular video input articulated representation skeleton-driven motion linear blend skinning hexplane-based refinement non-rigid deformations motion editing