Get it running now👉genrohub.com/blog/gen-human-…
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
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3 days to IROS 2026.
GenRobot.AI is getting ready to meet the researchers, builders, and innovators shaping the future of embodied AI in Pittsburgh.
We’re bringing our latest work on Human Data for Embodied AI to Booth 637.
Come explore how diverse, real-world human data can help scale Physical AI beyond the lab.
📍 Booth 637
📅 Sep 28–30
📌 Pittsburgh, PA See you at IROS.
#IROS2026 #EmbodiedAI #HumanData #PhysicalAI #Robotics
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Genrobot.AI retweeted
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
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Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
We are here to turn real-world human experience into training-ready data, designed to help models learn better.
Gen-HumanEgo is a start.
#EgoData #Opensource #EmbodiedAI
7
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6,847
Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning.
Powered by our Data Foundation Model (DFM), synchronized Ego video is transformed into training-ready signals: video, action, robust hand tracking, depth, semantic annotations are precisely aligned and encoded into unified tokens — creating a shared representation.
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Open-source now: huggingface.co/datasets/genr…
Join our Discord community to connect with the team and other builders: discord.gg/rSSb5thgu
Contact Us: opendata@genrobot.ai
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Swinging. Turning. Jumping.
@GenrobotAI DFM turns six-camera Ego video into continuous whole-body mesh and skeleton data, preserving body structure and temporal consistency even during fast motion and complex poses.
See the Whole Body. Learn the Whole Skill.
#GenRobot #WholeBodyData #egodata
#PhysicalAI #Robotics
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Bending. Squatting. Moving.
DFM reconstructs continuous whole-body meshes from Ego video, even with partial occlusion.
~3 cm mean whole-body error.
See the Whole Body. Learn the Whole Skill.
#GenRobot#WholeBodyData#ego data
#PhysicalAI #Robotics
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IROS 2026｜Meet @GenrobotAI in Pittsburgh – Human Data for Embodied Intelligence
We are excited to announce our participation in IROS 2026! We warmly invite researchers, industry leaders, and innovation partners from around the world to join us in Pittsburgh. Together, we'll delve into the frontier of embodied AI, explore breakthroughs in perception-action integration, and discuss pathways to real-world impact across industries.
📅 Date: September 28–30, 2026
📍 Venue: David L. Lawrence Convention Center, Pittsburgh, USA
📌 Booth: 637
We look forward to connecting with you in Pittsburgh — and exploring the future of embodied intelligence through Human Data together!
#Genrobot #humandata #egodata
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Genrobot.AI retweeted
Reliable Whole-Body Data is more than a human-looking mesh.
It requires accurate ground truth, temporally consistent motion, and a production pipeline built to scale.
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Reliable Whole-Body Data is more than a human-looking mesh.
It requires accurate ground truth, temporally consistent motion, and a production pipeline built to scale.
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😄Our internal evaluations show:
<30s on-site calibration
<0.4 px reprojection error
Built on this ground truth, DFM（Data Foundation Model） reconstructs continuous whole-body motion from partial egocentric observations.
~3 cm mean full-body reconstruction error
~2 cm upper body / ~3.5 cm lower body
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And the output goes beyond body mesh: whole-body motion, two-hand tracking, objects, contact states, egocentric observations, and action semantics—all aligned in one shared spatiotemporal coordinate system. From ingestion and reconstruction to quality validation, frame filtering, and training-format export, the entire pipeline is automated. Watch the video to see whole-body motion captured during a music practice session.
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Read more about our blog post👉：genrobot.ai/blog/whole-body
How do you scale whole-body data?
😜Start with Ego！
Vision-only，whole body mesh！
≈3 cm whole-body error
100K hours/month.
From real-world human behavior to policy-ready Whole-Body Manipulation Data—at scale.
See the Whole Body.
Learn the Whole Skill.
#PhysicalAI #Robotics
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Genrobot.AI retweeted
How do you scale whole-body data?
😜Start with Ego！
Vision-only，whole body mesh！
≈3 cm whole-body error
100K hours/month.
From real-world human behavior to policy-ready Whole-Body Manipulation Data—at scale.
See the Whole Body.
Learn the Whole Skill.
#PhysicalAI #Robotics
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How do you scale whole-body data?
😜Start with Ego！
Vision-only，whole body mesh！
≈3 cm whole-body error
100K hours/month.
From real-world human behavior to policy-ready Whole-Body Manipulation Data—at scale.
See the Whole Body.
Learn the Whole Skill.
#PhysicalAI #Robotics
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Head. Hands. Whole body. And a whole lot of Human Data. 🙌
At WAIC 2026, @GenRobotAI showcased how real-world human experience can be captured and transformed into high-quality, scalable data for Physical AI.
Let’s rewind the highlights! 🎬#WAIC2026 #GenrobotAI #HumanData
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Excited to see LingBot-VLA 2.0 open-sourced by @Robbyant. We're proud to have contributed the human data behind it — egocentric video paired with <1 cm hand tracking captured in the wild at scale and processed through our Data Foundation Model. #EmbodiedAI #Robotics
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