Rigel3D jointly generates rigged 3D meshes with geometry, skeleton topology, joint positions, and skinning weights using coupled surface and skeleton latent representations for image-conditioned animation-ready asset synthesis.
Anytop: Character animation diffusion with any topology
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
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UNVERDICTED 4representative citing papers
MoCapAnything V2 presents the first end-to-end learnable Video-to-Pose and Pose-to-Rotation framework for monocular arbitrary-skeleton motion capture by conditioning on a reference pose-rotation pair.
MoCapAnything reconstructs asset-specific BVH animations from monocular video by predicting 3D joint trajectories then applying constraint-aware inverse kinematics guided by a reference prompt encoder.
X-Morph retargets human motions to kinematically plausible references for multiple legged morphologies, trains privileged RL trackers, and distills them into deployable policies that generalize and enable teleoperation and text-conditioned generation.
citing papers explorer
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Rigel3D: Rig-aware Latents for Animation-Ready 3D Asset Generation
Rigel3D jointly generates rigged 3D meshes with geometry, skeleton topology, joint positions, and skinning weights using coupled surface and skeleton latent representations for image-conditioned animation-ready asset synthesis.
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MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons
MoCapAnything V2 presents the first end-to-end learnable Video-to-Pose and Pose-to-Rotation framework for monocular arbitrary-skeleton motion capture by conditioning on a reference pose-rotation pair.
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MoCapAnything: Unified 3D Motion Capture for Arbitrary Skeletons from Monocular Videos
MoCapAnything reconstructs asset-specific BVH animations from monocular video by predicting 3D joint trajectories then applying constraint-aware inverse kinematics guided by a reference prompt encoder.
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X-Morph: Human Motion Priors for Scalable Robot Learning Across Morphologies
X-Morph retargets human motions to kinematically plausible references for multiple legged morphologies, trains privileged RL trackers, and distills them into deployable policies that generalize and enable teleoperation and text-conditioned generation.