# Skeleton-free Pose Transfer for Stylized 3D Characters

arXiv: https://arxiv.org/abs/2208.00790 · HTML: https://mlsanity.com/paper/2208.00790/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- Builds on 26 of its 55 references that are in the map.
- First posted on arXiv 28 Jul 2022.

## Builds on (most cited first, 26 of 26)

- [AMASS: Archive of Motion Capture as Surface Shapes](https://mlsanity.com/paper/1904.03278/) (2019)
- [First Order Motion Model for Image Animation](https://mlsanity.com/paper/2003.00196/) (2020)
- [Motion Representations for Articulated Animation](https://mlsanity.com/paper/2104.11280/) (2021)
- [Multi-Garment Net: Learning to Dress 3D People from Images](https://mlsanity.com/paper/1908.06903/) (2019)
- [Animating Arbitrary Objects via Deep Motion Transfer](https://mlsanity.com/paper/1812.08861/) (2018)
- [SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks](https://mlsanity.com/paper/2104.03313/) (2021)
- [3D-CODED : 3D Correspondences by Deep Deformation](https://mlsanity.com/paper/1806.05228/) (2018)
- [COUCH: Towards Controllable Human-Chair Interactions](https://mlsanity.com/paper/2205.00541/) (2022)
- [Skeleton-Aware Networks for Deep Motion Retargeting](https://mlsanity.com/paper/2005.05732/) (2020)
- [Unsupervised Learning of Object Landmarks through Conditional Image Generation](https://mlsanity.com/paper/1806.07823/) (2018)
- [SCOPS: Self-Supervised Co-Part Segmentation](https://mlsanity.com/paper/1905.01298/) (2019)
- [Neural Kinematic Networks for Unsupervised Motion Retargetting](https://mlsanity.com/paper/1804.05653/) (2018)
- [Variational Autoencoders for Deforming 3D Mesh Models](https://mlsanity.com/paper/1709.04307/) (2017)
- [Unsupervised Shape and Pose Disentanglement for 3D Meshes](https://mlsanity.com/paper/2007.11341/) (2020)
- [Learning Skeletal Articulations with Neural Blend Shapes](https://mlsanity.com/paper/2105.02451/) (2021)
- [KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control](https://mlsanity.com/paper/2104.11224/) (2021)
- [Predicting Animation Skeletons for 3D Articulated Models via Volumetric Nets](https://mlsanity.com/paper/1908.08506/) (2019)
- [Neural Pose Transfer by Spatially Adaptive Instance Normalization](https://mlsanity.com/paper/2003.07254/) (2020)
- [DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates](https://mlsanity.com/paper/2102.09105/) (2021)
- [Contact-Aware Retargeting of Skinned Motion](https://mlsanity.com/paper/2109.07431/) (2021)
- [3D Pose Transfer with Correspondence Learning and Mesh Refinement](https://mlsanity.com/paper/2109.15025/) (2021)
- [Motion-supervised Co-Part Segmentation](https://mlsanity.com/paper/2004.03234/) (2020)
- [Skeleton Merger: an Unsupervised Aligned Keypoint Detector](https://mlsanity.com/paper/2103.10814/) (2021)
- [Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets](https://mlsanity.com/paper/2003.07619/) (2020)
- [Sparse Data Driven Mesh Deformation](https://mlsanity.com/paper/1709.01250/) (2017)
- [Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders](https://mlsanity.com/paper/2012.02459/) (2020)

## Built on by (most cited first, 30 of 30)

- [EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation](https://mlsanity.com/paper/2312.02256/) (2023)
- [MagicArticulate: Make Your 3D Models Articulation-Ready](https://mlsanity.com/paper/2502.12135/) (2025)
- [OmniMotionGPT: Animal Motion Generation with Limited Data](https://mlsanity.com/paper/2311.18303/) (2023)
- [MagicPose4D: Crafting Articulated Models with Appearance and Motion Control](https://mlsanity.com/paper/2405.14017/) (2024)
- [SAOR: Single-View Articulated Object Reconstruction](https://mlsanity.com/paper/2303.13514/) (2023)
- [TapMo: Shape-aware Motion Generation of Skeleton-free Characters](https://mlsanity.com/paper/2310.12678/) (2023)
- [CT4D: Consistent Text-to-4D Generation with Animatable Meshes](https://mlsanity.com/paper/2408.08342/) (2024)
- [Zero-shot Pose Transfer for Unrigged Stylized 3D Characters](https://mlsanity.com/paper/2306.00200/) (2023)
- [Weakly-supervised 3D Pose Transfer with Keypoints](https://mlsanity.com/paper/2307.13459/) (2023)
- [Pose-aware Attention Network for Flexible Motion Retargeting by Body Part](https://mlsanity.com/paper/2306.08006/) (2023)
- [Pose-to-Motion: Cross-Domain Motion Retargeting with Pose Prior](https://mlsanity.com/paper/2310.20249/) (2023)
- [PhysRig: Differentiable Physics-Based Skinning and Rigging Framework for Realistic Articulated Object Modeling](https://mlsanity.com/paper/2506.20936/) (2025)
- [PDT: Point Distribution Transformation with Diffusion Models](https://mlsanity.com/paper/2507.18939/) (2025)
- [Temporal Residual Jacobians For Rig-free Motion Transfer](https://mlsanity.com/paper/2407.14958/) (2024)
- [HMC: Hierarchical Mesh Coarsening for Skeleton-free Motion Retargeting](https://mlsanity.com/paper/2303.10941/) (2023)
- [VINECS: Video-based Neural Character Skinning](https://mlsanity.com/paper/2307.00842/) (2023)
- [Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses](https://mlsanity.com/paper/2406.09728/) (2024)
- [SMF: Template-free and Rig-free Animation Transfer using Kinetic Codes](https://mlsanity.com/paper/2504.04831/) (2025)
- [Motion Keyframe Interpolation for Any Human Skeleton via Temporally Consistent Point Cloud Sampling and Reconstruction](https://mlsanity.com/paper/2405.07444/) (2024)
- [Towards High-Quality 3D Motion Transfer with Realistic Apparel Animation](https://mlsanity.com/paper/2407.11266/) (2024)
- [Towards Robust 3D Pose Transfer with Adversarial Learning](https://mlsanity.com/paper/2404.02242/) (2024)
- [MAPConNet: Self-supervised 3D Pose Transfer with Mesh and Point Contrastive Learning](https://mlsanity.com/paper/2304.13819/) (2023)
- [ASMR: Adaptive Skeleton-Mesh Rigging and Skinning via 2D Generative Prior](https://mlsanity.com/paper/2503.13579/) (2025)
- [Advances and Trends in the 3D Reconstruction of the Shape and Motion of Animals](https://mlsanity.com/paper/2508.16062/) (2025)
- [ScanMove: Motion Prediction and Transfer for Unregistered Body Meshes](https://mlsanity.com/paper/2508.21095/) (2025)
- [MimiCAT: Mimic with Correspondence-Aware Cascade-Transformer for Category-Free 3D Pose Transfer](https://mlsanity.com/paper/2511.18370/) (2025)
- [MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos](https://mlsanity.com/paper/2601.02716/) (2026)
- [DSFFNet: Dual-Side Feature Fusion Network for 3D Pose Transfer](https://mlsanity.com/paper/2305.14951/) (2023)
- [BLARM: Animating 3D Objects from Video via Blending Latent Rigid Motion Primitives](https://mlsanity.com/paper/2608.31113/) (2026)
- [Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completion](https://mlsanity.com/paper/2610.18871/) (2026)

## Abstract (arXiv)

We present the first method that automatically transfers poses between stylized 3D characters without skeletal rigging. In contrast to previous attempts to learn pose transformations on fixed or topology-equivalent skeleton templates, our method focuses on a novel scenario to handle skeleton-free characters with diverse shapes, topologies, and mesh connectivities. The key idea of our method is to represent the characters in a unified articulation model so that the pose can be transferred through the correspondent parts. To achieve this, we propose a novel pose transfer network that predicts the character skinning weights and deformation transformations jointly to articulate the target character to match the desired pose. Our method is trained in a semi-supervised manner absorbing all existing character data with paired/unpaired poses and stylized shapes. It generalizes well to unseen stylized characters and inanimate objects. We conduct extensive experiments and demonstrate the effectiveness of our method on this novel task.