MoZoo generates high-fidelity animal videos with fur and muscle dynamics from coarse meshes by extending video diffusion with role-aware RoPE and asymmetric decoupled attention, trained on a new synthetic-to-real dataset.
arXiv preprint arXiv:2506.07489 (2025)
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
ACT is a trajectory-conditioned framework for topology-general skeletal animation that injects 3D point trajectories from monocular video into skeletons via a Routed Trajectory Injector for improved fidelity and temporal consistency.
A training-free Spatio-Temporal Attention Chain framework accelerates 4D mesh generation 13x, improves quality, scales to 16x longer videos, and supports downstream tracking and camera estimation.
SkelMo introduces a category-agnostic diffusion framework for skeletal motion generation from 2D videos, trained on a new dataset of ~20,000 rigged 3D animations with a structural-semantic injection mechanism.
citing papers explorer
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MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation
MoZoo generates high-fidelity animal videos with fur and muscle dynamics from coarse meshes by extending video diffusion with role-aware RoPE and asymmetric decoupled attention, trained on a new synthetic-to-real dataset.
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Follow Your Track: Precise Skeleton Animation Controlled by 3D Trajectories
ACT is a trajectory-conditioned framework for topology-general skeletal animation that injects 3D point trajectories from monocular video into skeletons via a Routed Trajectory Injector for improved fidelity and temporal consistency.
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Fast 4D Mesh Generation by Spatio-Temporal Attention Chains
A training-free Spatio-Temporal Attention Chain framework accelerates 4D mesh generation 13x, improves quality, scales to 16x longer videos, and supports downstream tracking and camera estimation.
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SkelMo: Universal Skeletal Motion Generation for 3D Rigged Shapes
SkelMo introduces a category-agnostic diffusion framework for skeletal motion generation from 2D videos, trained on a new dataset of ~20,000 rigged 3D animations with a structural-semantic injection mechanism.