# Contact-Aware Retargeting of Skinned Motion arXiv: https://arxiv.org/abs/2109.07431 ยท HTML: https://mlsanity.com/paper/2109.07431/ ## Key facts - Cited by 32 papers in the map (data through 14 Oct 2026). - Builds on 12 of its 33 references that are in the map. - First posted on arXiv 15 Sep 2021. ## Builds on (most cited first, 12 of 12) - [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016) - [Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop](https://mlsanity.com/paper/1909.12828/) (2019) - [Learning joint reconstruction of hands and manipulated objects](https://mlsanity.com/paper/1904.05767/) (2019) - [Resolving 3D Human Pose Ambiguities with 3D Scene Constraints](https://mlsanity.com/paper/1908.06963/) (2019) - [Generating 3D People in Scenes without People](https://mlsanity.com/paper/1912.02923/) (2019) - [Skeleton-Aware Networks for Deep Motion Retargeting](https://mlsanity.com/paper/2005.05732/) (2020) - [Capturing Hands in Action using Discriminative Salient Points and Physics Simulation](https://mlsanity.com/paper/1506.02178/) (2015) - [Contact and Human Dynamics from Monocular Video](https://mlsanity.com/paper/2007.11678/) (2020) - [On Self-Contact and Human Pose](https://mlsanity.com/paper/2104.03176/) (2021) - [Neural Kinematic Networks for Unsupervised Motion Retargetting](https://mlsanity.com/paper/1804.05653/) (2018) - [Learning Character-Agnostic Motion for Motion Retargeting in 2D](https://mlsanity.com/paper/1905.01680/) (2019) - [Dense Human Body Correspondences Using Convolutional Networks](https://mlsanity.com/paper/1511.05904/) (2015) ## Built on by (most cited first, 30 of 32) - [3D Human Pose Estimation via Intuitive Physics](https://mlsanity.com/paper/2303.18246/) (2023) - [InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions](https://mlsanity.com/paper/2502.20390/) (2025) - [AnyTop: Character Animation Diffusion with Any Topology](https://mlsanity.com/paper/2502.17327/) (2025) - [Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry](https://mlsanity.com/paper/2303.08658/) (2023) - [Skeleton-free Pose Transfer for Stylized 3D Characters](https://mlsanity.com/paper/2208.00790/) (2022) - [Action-conditioned On-demand Motion Generation](https://mlsanity.com/paper/2207.08164/) (2022) - [LAC: Latent Action Composition for Skeleton-based Action Segmentation](https://mlsanity.com/paper/2308.14500/) (2023) - [UnifiedGesture: A Unified Gesture Synthesis Model for Multiple Skeletons](https://mlsanity.com/paper/2309.07051/) (2023) - [Zero-shot Pose Transfer for Unrigged Stylized 3D Characters](https://mlsanity.com/paper/2306.00200/) (2023) - [Skinned Motion Retargeting with Dense Geometric Interaction Perception](https://mlsanity.com/paper/2410.20986/) (2024) - [4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements](https://mlsanity.com/paper/2306.07399/) (2023) - [ImitationNet: Unsupervised Human-to-Robot Motion Retargeting via Shared Latent Space](https://mlsanity.com/paper/2309.05310/) (2023) - [Shape My Moves: Text-Driven Shape-Aware Synthesis of Human Motions](https://mlsanity.com/paper/2504.03639/) (2025) - [Pose-aware Attention Network for Flexible Motion Retargeting by Body Part](https://mlsanity.com/paper/2306.08006/) (2023) - [Physics-based Motion Retargeting from Sparse Inputs](https://mlsanity.com/paper/2307.01938/) (2023) - [Pose-to-Motion: Cross-Domain Motion Retargeting with Pose Prior](https://mlsanity.com/paper/2310.20249/) (2023) - [Correspondence-free online human motion retargeting](https://mlsanity.com/paper/2302.00556/) (2023) - [Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction](https://mlsanity.com/paper/2402.04768/) (2024) - [Diffusion-based Human Motion Style Transfer with Semantic Guidance](https://mlsanity.com/paper/2405.06646/) (2024) - [HMC: Hierarchical Mesh Coarsening for Skeleton-free Motion Retargeting](https://mlsanity.com/paper/2303.10941/) (2023) - [Semantics-aware Motion Retargeting with Vision-Language Models](https://mlsanity.com/paper/2312.01964/) (2023) - [Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses](https://mlsanity.com/paper/2406.09728/) (2024) - [Two-Person Interaction Augmentation with Skeleton Priors](https://mlsanity.com/paper/2404.05490/) (2024) - [I-CTRL: Imitation to Control Humanoid Robots Through Constrained Reinforcement Learning](https://mlsanity.com/paper/2405.08726/) (2024) - [An Identity-Preserved Framework for Human Motion Transfer](https://mlsanity.com/paper/2204.06862/) (2022) - [ASMR: Adaptive Skeleton-Mesh Rigging and Skinning via 2D Generative Prior](https://mlsanity.com/paper/2503.13579/) (2025) - [STaR: Seamless Spatial-Temporal Aware Motion Retargeting with Penetration and Consistency Constraints](https://mlsanity.com/paper/2504.06504/) (2025) - [ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting](https://mlsanity.com/paper/2605.06593/) (2026) - [MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos](https://mlsanity.com/paper/2601.02716/) (2026) - [UniCon3R: Unified Contact-aware 4D Human-Scene Reconstruction from Monocular Video](https://mlsanity.com/paper/2604.19923/) (2026) ## Abstract (arXiv) This paper introduces a motion retargeting method that preserves self-contacts and prevents interpenetration. Self-contacts, such as when hands touch each other or the torso or the head, are important attributes of human body language and dynamics, yet existing methods do not model or preserve these contacts. Likewise, interpenetration, such as a hand passing into the torso, are a typical artifact of motion estimation methods. The input to our method is a human motion sequence and a target skeleton and character geometry. The method identifies self-contacts and ground contacts in the input motion, and optimizes the motion to apply to the output skeleton, while preserving these contacts and reducing interpenetration. We introduce a novel geometry-conditioned recurrent network with an encoder-space optimization strategy that achieves efficient retargeting while satisfying contact constraints. In experiments, our results quantitatively outperform previous methods and we conduct a user study where our retargeted motions are rated as higher-quality than those produced by recent works. We also show our method generalizes to motion estimated from human videos where we improve over previous works that produce noticeable interpenetration.