mlsanityData to 14 Oct 2026

Category-Agnostic Neural Object Rigging

arXiv 2505.20283 ↗First posted 26 May 2025cs.CVcited by 9

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Abstract (arXiv)

The motion of deformable 4D objects lies in a low-dimensional manifold. To better capture the low dimensionality and enable better controllability, traditional methods have devised several heuristic-based methods, i.e., rigging, for manipulating dynamic objects in an intuitive fashion. However, such representations are not scalable due to the need for expert knowledge of specific categories. Instead, we study the automatic exploration of such low-dimensional structures in a purely data-driven manner. Specifically, we design a novel representation that encodes deformable 4D objects into a sparse set of spatially grounded blobs and an instance-aware feature volume to disentangle the pose and instance information of the 3D shape. With such a representation, we can manipulate the pose of 3D objects intuitively by modifying the parameters of the blobs, while preserving rich instance-specific information. We evaluate the proposed method on a variety of object categories and demonstrate the effectiveness of the proposed framework. Project page: https://guangzhaohe.com/canor

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 41 of its 59 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

41 of 59 references.

References · 41

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Point Transformercited by 1,470
  3. 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
  4. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 695
  5. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 458
  6. 20163D Menagerie: Modeling the 3D shape and pose of animalscited by 312
  7. 20193D Morphable Face Models -- Past, Present and Futurecited by 270
  8. 2024Shape of Motion: 4D Reconstruction from a Single Videocited by 250
  9. 2023Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representationcited by 228
  10. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 197
  11. 2024MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffoldscited by 179
  12. 2021Self-attention Does Not Need O(n2) Memorycited by 154
29 more
  1. 20214DComplete: Non-Rigid Motion Estimation Beyond the Observable Surfacecited by 124
  2. 2023GART: Gaussian Articulated Template Modelscited by 121
  3. 2019Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapescited by 119
  4. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 112
  5. 2019Neural Cages for Detail-Preserving 3D Deformationscited by 106
  6. 2024Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videoscited by 97
  7. 2021NPMs: Neural Parametric Models for 3D Deformable Shapescited by 90
  8. 2022Learning Neural Parametric Head Modelscited by 73
  9. 2023Learning Neural Volumetric Representations of Dynamic Humans in Minutescited by 70
  10. 2020Neural Deformation Graphs for Globally-consistent Non-rigid Reconstructioncited by 67
  11. 2022LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discoverycited by 66
  12. 2020Unsupervised Shape and Pose Disentanglement for 3D Meshescited by 61
  13. 2021DOVE: Learning Deformable 3D Objects by Watching Videoscited by 61
  14. 20193DN: 3D Deformation Networkcited by 60
  15. 2021KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Controlcited by 51
  16. 2022Non-rigid Point Cloud Registration with Neural Deformation Pyramidcited by 42
  17. 2021ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generatorscited by 40
  18. 2019Predicting Animation Skeletons for 3D Articulated Models via Volumetric Netscited by 39
  19. 2021DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinatescited by 37
  20. 2022BlobGAN: Spatially Disentangled Scene Representationscited by 35
  21. 2023Building Rearticulable Models for Arbitrary 3D Objects from 4D Point Cloudscited by 34
  22. 2023Instant Multi-View Head Capture through Learnable Registrationcited by 34
  23. 2022Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemblecited by 31
  24. 2022SPAMs: Structured Implicit Parametric Modelscited by 29
  25. 2023Neural Face Rigging for Animating and Retargeting Facial Meshes in the Wildcited by 25
  26. 2023As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priorscited by 25
  27. 2022Morig: Motion-aware rigging of character meshes from point cloudscited by 20
  28. 2022Unsupervised Image Representation Learning with Deep Latent Particlescited by 19
  29. 2024Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Posescited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 9.

9 papers.

  1. 2026Motion 3-to-4: 3D Motion Reconstruction for 4D Synthesiscited by 15
  2. 2026Choreographing a World of Dynamic Objectscited by 5
  3. 2026BiMotion: B-spline Motion for Text-guided Dynamic 3D Character Generationcited by 4
  4. 2026NeuROK: Generative 4D Neural Object Kinematicscited by 3
  5. 2026SPRig: Self-Supervised Pose-Invariant Rigging from Mesh Sequencescited by 1
  6. 2026Rigel3D: Rig-aware Latents for Animation-Ready 3D Asset Generationcited by 0
  7. 2026LaGSplat: Inferring Physics-Governed Interactive Simulation from Monocular Video Using Latent Lagrangian Gaussian Splattingcited by 0
  8. 2026BLARM: Animating 3D Objects from Video via Blending Latent Rigid Motion Primitivescited by 0
  9. 2026Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completioncited by 0