# EmbodiSwap for Zero-Shot Robot Imitation Learning

arXiv: https://arxiv.org/abs/2510.03706 · HTML: https://mlsanity.com/paper/2510.03706/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data.
- Builds on 30 of its 37 references that are in the map.
- First posted on arXiv 4 Oct 2025.

## Placed in

- Offline RL and imitation learning from data / [Robot manipulation imitation learning](https://mlsanity.com/offlinerl/robot-manipulation-imitation-learning/)

## Builds on (most cited first, 30 of 30)

- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [SAM 2: Segment Anything in Images and Videos](https://mlsanity.com/paper/2408.00714/) (2024)
- [π0: A Vision-Language-Action Flow Model for General Robot Control](https://mlsanity.com/paper/2410.24164/) (2024)
- [Ego4D: Around the World in 3,000 Hours of Egocentric Video](https://mlsanity.com/paper/2110.07058/) (2021)
- [Octo: An Open-Source Generalist Robot Policy](https://mlsanity.com/paper/2405.12213/) (2024)
- [R3M: A Universal Visual Representation for Robot Manipulation](https://mlsanity.com/paper/2203.12601/) (2022)
- [Rescaling Egocentric Vision](https://mlsanity.com/paper/2006.13256/) (2020)
- [VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training](https://mlsanity.com/paper/2210.00030/) (2022)
- [Vision-Language Foundation Models as Effective Robot Imitators](https://mlsanity.com/paper/2311.01378/) (2023)
- [HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction](https://mlsanity.com/paper/2203.01577/) (2022)
- [Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles](https://mlsanity.com/paper/2306.00989/) (2023)
- [Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?](https://mlsanity.com/paper/2303.18240/) (2023)
- [EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video](https://mlsanity.com/paper/2505.11709/) (2025)
- [UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler](https://mlsanity.com/paper/2502.20110/) (2025)
- [Data Scaling Laws in Imitation Learning for Robotic Manipulation](https://mlsanity.com/paper/2410.18647/) (2024)
- [EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations](https://mlsanity.com/paper/2209.13064/) (2022)
- [Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos](https://mlsanity.com/paper/2204.01696/) (2022)
- [Diagnosing Error in Temporal Action Detectors](https://mlsanity.com/paper/1807.10706/) (2018)
- [Phantom: Training Robots Without Robots Using Only Human Videos](https://mlsanity.com/paper/2503.00779/) (2025)
- [HaWoR: World-Space Hand Motion Reconstruction from Egocentric Videos](https://mlsanity.com/paper/2501.02973/) (2025)
- [Forecasting Action through Contact Representations from First Person Video](https://mlsanity.com/paper/2102.00649/) (2021)
- [Masquerade: Learning from In-the-wild Human Videos using Data-Editing](https://mlsanity.com/paper/2508.09976/) (2025)
- [Hand-Object Interaction Pretraining from Videos](https://mlsanity.com/paper/2409.08273/) (2024)
- [OmniEraser: Remove Objects and Their Effects in Images with Paired Video-Frame Data](https://mlsanity.com/paper/2501.07397/) (2025)
- [EgoZero: Robot Learning from Smart Glasses](https://mlsanity.com/paper/2505.20290/) (2025)
- [ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos](https://mlsanity.com/paper/2503.23877/) (2025)
- [Spatiotemporal Predictive Pre-training for Robotic Motor Control](https://mlsanity.com/paper/2403.05304/) (2024)
- [Transfer Learning in Robotics: An Upcoming Breakthrough? A Review of Promises and Challenges](https://mlsanity.com/paper/2311.18044/) (2023)
- [Novel Diffusion Models for Multimodal 3D Hand Trajectory Prediction](https://mlsanity.com/paper/2504.07375/) (2025)
- [Therbligs in Action: Video Understanding through Motion Primitives](https://mlsanity.com/paper/2304.03631/) (2023)

## Built on by (most cited first, 2 of 2)

- [HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos](https://mlsanity.com/paper/2605.24934/) (2026)
- [Cloak: Zero-Shot Cross-Embodiment Manipulation by Masking the End-Effector from the VLA](https://mlsanity.com/paper/2606.22836/) (2026)

## Abstract (arXiv)

We introduce EmbodiSwap - a method for producing photorealistic synthetic robot overlays over human video. We employ EmbodiSwap for zero-shot imitation learning, bridging the embodiment gap between in-the-wild ego-centric human video and a target robot embodiment. We train a closed-loop robot manipulation policy over the data produced by EmbodiSwap. We make novel use of V-JEPA as a visual backbone, repurposing V-JEPA from the domain of video understanding to imitation learning over synthetic robot videos. Adoption of V-JEPA outperforms alternative vision backbones more conventionally used within robotics. In real-world tests, our zero-shot trained V-JEPA model achieves an 82% success rate, outperforming a few-shot trained π0 network as well as π0 trained over data produced by EmbodiSwap. We release (i) code for generating the synthetic robot overlays which takes as input human videos and an arbitrary robot URDF and generates a robot dataset, (ii) the robot dataset we synthesize over EPIC-Kitchens, HOI4D and Ego4D, and (iii) model checkpoints and inference code, to facilitate reproducible research and broader adoption.