Articulated Kinematics Distillation from Video Diffusion Models
We present Articulated Kinematics Distillation (AKD), a framework for
generating high-fidelity character animations by merging the strengths of
skeleton-based animation and modern generative models. AKD uses a
skeleton-based representation for rigged 3D assets, drastically reducing the
Degrees of Freedom (DoFs) by focusing on joint-level control, which allows for
efficient, consistent motion synthesis. Through Score Distillation Sampling
(SDS) with pre-trained video diffusion models, AKD distills complex,
articulated motions while maintaining structural integrity, overcoming
challenges faced by 4D neural deformation fields in preserving shape
consistency. This approach is naturally compatible with physics-based
simulation, ensuring physically plausible interactions. Experiments show that
AKD achieves superior 3D consistency and motion quality compared with existing
works on text-to-4D generation. Project page:
https://research.nvidia.com/labs/dir/akd/
67edf4bf5e87fcaa485a0ad9
Xuan Li
admin_assigned
2025-04-03T14:04:06.298Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/6387064a2ee2261893d85c0e/LznJi69uQwm1Le5ma6Zb_.jpeg
xuan li
user
xuanli
67edf4bf5e87fcaa485a0ada
Qianli Ma
67edf4bf5e87fcaa485a0adb
Tsung-Yi Lin
admin_assigned
2025-04-03T14:03:42.992Z
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Tsung-Yi Lin
user
tsungyi
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Yongxin Chen
admin_assigned
2025-04-03T14:03:36.411Z
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Yongxin Chen
user
Ema11
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Chenfanfu Jiang
admin_assigned
2025-04-03T14:03:29.907Z
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Chenfanfu Jiang
user
cffjiang
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Ming-Yu Liu
admin_assigned
2025-04-03T14:03:21.297Z
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Ming-Yu Liu
user
mingyuliutw
67edf4bf5e87fcaa485a0adf
Donglai Xiang
Articulated Kinematics Distillation from Video Diffusion Models
We present Articulated Kinematics Distillation (AKD), a framework for
generating high-fidelity character animations by merging the strengths of
skeleton-based animation and modern generative models. AKD uses a
skeleton-based representation for rigged 3D assets, drastically reducing the
Degrees of Freedom (DoFs) by focusing on joint-level control, which allows for
efficient, consistent motion synthesis. Through Score Distillation Sampling
(SDS) with pre-trained video diffusion models, AKD distills complex,
articulated motions while maintaining structural integrity, overcoming
challenges faced by 4D neural deformation fields in preserving shape
consistency. This approach is naturally compatible with physics-based
simulation, ensuring physically plausible interactions. Experiments show that
AKD achieves superior 3D consistency and motion quality compared with existing
works on text-to-4D generation. Project page:
https://research.nvidia.com/labs/dir/akd/
Articulated Kinematics Distillation merges skeletal animation and diffusion models to generate high-fidelity, structurally consistent, and physically plausible character animations.
skeleton-based animation generative models Degrees of Freedom (DoFs) Score Distillation Sampling (SDS) video diffusion models shape consistency physics-based simulation