mlsanityData to 7 Oct 2026

Morig: Motion-aware rigging of character meshes from point clouds

arXiv 2210.09463 ↗First posted 17 Oct 2022cs.GR cs.CVcited by 20

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Abstract (arXiv)

We present MoRig, a method that automatically rigs character meshes driven by single-view point cloud streams capturing the motion of performing characters. Our method is also able to animate the 3D meshes according to the captured point cloud motion. MoRig's neural network encodes motion cues from the point clouds into features that are informative about the articulated parts of the performing character. These motion-aware features guide the inference of an appropriate skeletal rig for the input mesh, which is then animated based on the point cloud motion. Our method can rig and animate diverse characters, including humanoids, quadrupeds, and toys with varying articulation. It accounts for occluded regions in the point clouds and mismatches in the part proportions between the input mesh and captured character. Compared to other rigging approaches that ignore motion cues, MoRig produces more accurate rigs, well-suited for re-targeting motion from captured characters.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 17 of its 47 references that are in the map. First posted on arXiv 17 Oct 2022.

Builds on

17 of 47 references.

References · 17

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5 more
  1. 2021MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronizationcited by 46
  2. 2019Predicting Animation Skeletons for 3D Articulated Models via Volumetric Netscited by 39
  3. 2020RPM-Net: Recurrent Prediction of Motion and Parts from Point Cloudcited by 26
  4. 20193D Rigid Motion Segmentation with Mixed and Unknown Number of Modelscited by 11
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 1; 2025: 7; 2026: 9.

20 papers.

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  1. 2025MagicArticulate: Make Your 3D Models Articulation-Readycited by 43
  2. 2025Puppeteer: Rig and Animate Your 3D Modelscited by 41
  3. 2023As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priorscited by 24
  4. 2025iTACO: Interactable Digital Twins of Articulated Objects from Casually Captured RGBD Videoscited by 18
  5. 2023TapMo: Shape-aware Motion Generation of Skeleton-free Characterscited by 15
  6. 2025RigGS: Rigging of 3D Gaussians for Modeling Articulated Objects in Videoscited by 14
  7. 2024GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesiscited by 12
  8. 2025Category-Agnostic Neural Object Riggingcited by 8
  9. 2023Explorable Mesh Deformation Subspaces from Unstructured Generative Modelscited by 6
  10. 2026Skin Tokens: A Learned Compact Representation for Unified Autoregressive Riggingcited by 5
  11. 2025ARMO: Autoregressive Rigging for Multi-Category Objectscited by 4
  12. 2026AniGen: Unified S3 Fields for Animatable 3D Asset Generationcited by 3
8 more
  1. 2025ASMR: Adaptive Skeleton-Mesh Rigging and Skinning via 2D Generative Priorcited by 2
  2. 2026SPRig: Self-Supervised Pose-Invariant Rigging from Mesh Sequencescited by 1
  3. 2026ViP-Rig: Visual-Prompted Controllable Riggingcited by 1
  4. 2026GaussiAnimate: Rig Animatable Categories with Level of Dynamicscited by 0
  5. 2026Rigel3D: Rig-aware Latents for Animation-Ready 3D Asset Generationcited by 0
  6. 2026RigPAPR: Rig-Based Animation of Static Neural Point Clouds from a Fixed-Viewpoint Videocited by 0
  7. 2026BLARM: Animating 3D Objects from Video via Blending Latent Rigid Motion Primitivescited by 0
  8. 2026Branch-Centric Tokenization and Test-Time Augmentation for Skeleton Generationcited by 0