EgoSteer-3B-RealMan is the generalist policy from EgoSteer: A Full-Stack System Towards Steerable Dexterous Manipulation from Egocentric Videos. It is a world-model-enhanced Vision-Language-Action (VLA) policy built on a Qwen3-VL backbone with a flow-matching action expert, post-trained from EgoSteer-3B-Base on real-world demonstrations collected on the RealMan robot. This is a robot-ready dual-camera (head + chest) checkpoint, corresponding to EgoSteer-9.6K-DG in the paper. For the base model to fine-tune on your own data, see EgoSteer-3B-Base. Our full-stack system integrates EgoSmith (data pipeline), Robot Stack (deployment), and EgoSteer (policy) to learn from 9.6k hours of large-scale…
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EgoSteer
EgoSteer
Models in Library2
Datasets in Library0
Models on Hugging Face2
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Published tasks: Robotics.
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Models
EgoSteer-3B-Base is the base world-model-enhanced Vision-Language-Action (VLA) policy from EgoSteer: A Full-Stack System Towards Steerable Dexterous Manipulation from Egocentric Videos. It is built on a Qwen3-VL backbone with a flow-matching action expert and a DINOv3 latent future-prediction objective used only during training, and learns a unified human-to-robot action space from large-scale egocentric human videos. This is the pretrained base checkpoint, corresponding to EgoSteer-9.6K-PT in the paper. For a robot-ready generalist, see Our full-stack system integrates EgoSmith (data pipeline), Robot Stack (deployment), and EgoSteer (policy) to learn from 9.6k hours of large-scale…