# HDMI: Learning Interactive Humanoid Whole-Body Control from Human Videos

arXiv: https://arxiv.org/abs/2509.16757 · HTML: https://mlsanity.com/paper/2509.16757/

## Key facts

- Cited by 38 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2025.

## Built on by (most cited first, 30 of 38)

- [SPIDER: Scalable Physics-Informed Dexterous Retargeting](https://mlsanity.com/paper/2511.09484/) (2025)
- [TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning](https://mlsanity.com/paper/2510.00739/) (2025)
- [Opening the Sim-to-Real Door for Humanoid Pixel-to-Action Policy Transfer](https://mlsanity.com/paper/2512.01061/) (2025)
- [HumanX: Toward Agile and Generalizable Humanoid Interaction Skills from Human Videos](https://mlsanity.com/paper/2602.02473/) (2026)
- [HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation](https://mlsanity.com/paper/2604.07993/) (2026)
- [Humanoid Goalkeeper: Learning from Position Conditioned Task-Motion Constraints](https://mlsanity.com/paper/2510.18002/) (2025)
- [ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation](https://mlsanity.com/paper/2603.03279/) (2026)
- [RoboMirror: Understand Before You Imitate for Video to Humanoid Locomotion](https://mlsanity.com/paper/2512.23649/) (2025)
- [Learning Whole-Body Human-Humanoid Interaction from Human-Human Demonstrations](https://mlsanity.com/paper/2601.09518/) (2026)
- [MeshMimic: Geometry-Aware Humanoid Motion Learning through 3D Scene Reconstruction](https://mlsanity.com/paper/2602.15733/) (2026)
- [SteadyTray: Learning Object Balancing Tasks in Humanoid Tray Transport via Residual Reinforcement Learning](https://mlsanity.com/paper/2603.10306/) (2026)
- [Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action](https://mlsanity.com/paper/2605.22283/) (2026)
- [SceneBot: Contact-Prompted General Humanoid Whole Body Tracking with Scene-Interaction](https://mlsanity.com/paper/2606.27581/) (2026)
- [Learning Human-Like Badminton Skills for Humanoid Robots](https://mlsanity.com/paper/2602.08370/) (2026)
- [SUGAR: A Scalable Human-Video-Driven Generalizable Humanoid Loco-Manipulation Learning Framework](https://mlsanity.com/paper/2605.20373/) (2026)
- [SplitAdapter: Load-Aware Humanoid Loco-Manipulation via Factorized Adaptation](https://mlsanity.com/paper/2606.03297/) (2026)
- [REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning](https://mlsanity.com/paper/2603.13707/) (2026)
- [Imagine2Real: Towards Zero-shot Humanoid-Object Interaction via Video Generative Priors](https://mlsanity.com/paper/2605.22272/) (2026)
- [Scaling Behavior Foundation Model for Humanoid Robots](https://mlsanity.com/paper/2607.15163/) (2026)
- [AdaptManip: Learning Adaptive Whole-Body Object Lifting and Delivery with Online Recurrent State Estimation](https://mlsanity.com/paper/2602.14363/) (2026)
- [Generalizing from References using a Multi-Task Reference and Goal-Driven RL Framework](https://mlsanity.com/paper/2602.20375/) (2026)
- [EmbodMocap: In-the-Wild 4D Human-Scene Reconstruction for Embodied Agents](https://mlsanity.com/paper/2602.23205/) (2026)
- [DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors](https://mlsanity.com/paper/2604.00202/) (2026)
- [RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning](https://mlsanity.com/paper/2606.11092/) (2026)
- [AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance](https://mlsanity.com/paper/2606.29209/) (2026)
- [Weave: Learning Whole-Body Dexterous Loco-Manipulation from Human-Object Interactions](https://mlsanity.com/paper/2609.16683/) (2026)
- [CRISP: Contact-Guided Real2Sim from Monocular Video with Planar Scene Primitives](https://mlsanity.com/paper/2512.14696/) (2025)
- [LadderMan: Learning Humanoid Perceptive Ladder Climbing](https://mlsanity.com/paper/2606.05873/) (2026)
- [TaskNPoint: How to Teach Your Humanoid to Hit a Backhand in Minutes](https://mlsanity.com/paper/2606.26215/) (2026)
- [LUCID: Latent-Skill Unified Control via Imagined Dynamics for Long-Horizon Humanoid Loco-Manipulation](https://mlsanity.com/paper/2608.07746/) (2026)

## Abstract (arXiv)

Enabling robust whole-body humanoid-object interaction (HOI) remains challenging due to motion data scarcity and the contact-rich nature. We present HDMI (HumanoiD iMitation for Interaction), a simple and general framework that learns whole-body humanoid-object interaction skills directly from monocular RGB videos. Our pipeline (i) extracts and retargets human and object trajectories from unconstrained videos to build structured motion datasets, (ii) trains a reinforcement learning (RL) policy to co-track robot and object states with three key designs: a unified object representation, a residual action space, and a general interaction reward, and (iii) zero-shot deploys the RL policies on real humanoid robots. Extensive sim-to-real experiments on a Unitree G1 humanoid demonstrate the robustness and generality of our approach: HDMI achieves 67 consecutive door traversals and successfully performs 6 distinct loco-manipulation tasks in the real world and 14 tasks in simulation. Our results establish HDMI as a simple and general framework for acquiring interactive humanoid skills from human videos.