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Introducing Gen-HumanEgo, a more training-ready open-source egocentric human data for robot learning. We are here to turn real-world human experience into training-ready data, designed to help models learn better. Gen-HumanEgo is a start. Open source now on HuggingFace.

Genrobot.AI

1,346 subscribers

1,667,302 次观看 • 1 个月前 •via X (Twitter)

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老王视觉p图设计的头像

老王视觉p图设计1 个月前

开源了？链接发一下，我去看看数据质量咋样。

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1/ 🧠Humans are the best robot data source! 2/ 👓Human egocentric video is rich in quantity, but poor in quality. 3/ Beyond scaling data, smarter representation and architecture matter just as much. 4/ Want an open-source framework to train your own learn-from-human-data robot policy? 🚀We introduce HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Robot-Data-Free ✦ Just 30 min of data per task ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Easy-to-Implement Let's squeeze every bit of signal out of human data! 🌐 Website: 📄 Paper: 💻 Code: 📹 Video: 🧵 1/n

1/ 🧠Humans are the best robot data source! 2/ 👓Human egocentric video is rich in quantity, but poor in quality. 3/ Beyond scaling data, smarter representation and architecture matter just as much. 4/ Want an open-source framework to train your own learn-from-human-data robot policy? 🚀We introduce HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Robot-Data-Free ✦ Just 30 min of data per task ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Easy-to-Implement Let's squeeze every bit of signal out of human data! 🌐 Website: 📄 Paper: 💻 Code: 📹 Video: 🧵 1/n

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We built a robotics data engine with Astra-level performance at 125x lower cost. And we are open-sourcing the weights today! Introducing Flora, a suite of open models to parse the physical world and turn raw footage into rich training signals. Flora already powers our in-house data engine, labeling 200K hours of videos a day on 500 GPUs. We created it to scale the frontier for robot learning. Now you own the weights too. Flora gives you: - High-quality, timestamped captions to curate and filter human egocentric and robot data; - Dense progress rewards for quality control and RL post-training; - Rubrics scoring for real-world benchmarking Try it today, links in thread:

We built a robotics data engine with Astra-level performance at 125x lower cost. And we are open-sourcing the weights today! Introducing Flora, a suite of open models to parse the physical world and turn raw footage into rich training signals. Flora already powers our in-house data engine, labeling 200K hours of videos a day on 500 GPUs. We created it to scale the frontier for robot learning. Now you own the weights too. Flora gives you: - High-quality, timestamped captions to curate and filter human egocentric and robot data; - Dense progress rewards for quality control and RL post-training; - Rubrics scoring for real-world benchmarking Try it today, links in thread:

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ego-to-robot data pipeline is one key component of Qwen-RobotManip （ Today, we’re sharing the full technical details behind it: Ego2Robot 🤖 It turns egocentric human videos into scalable robot training data and improves VLA generalization across tasks and embodiments. page: arxiv: huggingface upvoting 🚀:

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Figure

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23,562 次观看 • 3 个月前

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Data is the core bottleneck for robotics, here is the solution: Introducing MicroAGI00: We open sourced 1M+ frames of egocentric human long horizon mobile manipulation data. Scaling to 300M by Dec '25 and 100B frames Q4 2026 dm if you want your robot to wipe your office 🧵

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39,646 次观看 • 1 年前

So I heard we need more data for robot learning :) Purely real world teleop is expensive and slow, making large scale data collection challenging. I’ve been excited about getting more data into robot learning, going beyond just real-world teleop data. To this end, we’ve been scaling up data generation with RL in realistic simulations generated on the fly from crowdsourced videos. Enables realistic data collection, much more cheaply than purely real world teleop. Importantly, data collection becomes even*cheaper* with more environments, allowing training with over 100x more data. Transfers to real robots for generalizable manipulation. A 🧵 (1/N)

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13,358 次观看 • 1 年前

Robotics has a data problem, and egocentric data is a compelling way to solve it because egocentric data is (1) scalable — it’s cheap to collect — and (2) easily captures the breadth and diversity of real human tasks, while (3) being true to real physics. Lightwheel recently released a hundred thousand hours of high-quality egocentric video data, spread across a wide range of human tasks from cleaning and tidying to assembly and construction to retail tasks. Here to tell us about this tremendous effort is Steve Xie, CEO and co-founder of Lightwheel. The data is also available on HuggingFace right now. Watch Episode 102 of RoboPapers, with Michael Cho - Rbt/Acc and Jiafei Duan, to learn more!

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Privacy-first research is the core of everything we do at Project Aria. 🛡️✨ We’re thrilled to release EgoBlur Gen 2—our next-gen open-source solution for preserving privacy in egocentric video. Key Features: ✅ Optimized for Gen 2! Tuned for high-res data & next-gen hardware ⚡️ ✅ Native for VRS, MP4, JPEG, and PNG EgoBlur Gen 2 helps you automatically detect and obscure faces and license plates on egocentric cameras from Aria Gen 2 with ease. 🔍 Dive into the models: 👉

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20,362 次观看 • 5 个月前

We got a robot to clean up homes that were never seen in its training data! Our new model, π-0.5, aims to tackle open-world generalization. We took our robot into homes that were not in the training data and asked it to clean kitchens and bedrooms. More below⤵️

We got a robot to clean up homes that were never seen in its training data! Our new model, π-0.5, aims to tackle open-world generalization. We took our robot into homes that were not in the training data and asked it to clean kitchens and bedrooms. More below⤵️

Physical Intelligence

552,530 次观看 • 1 年前

Training robots for the open world needs diverse data But collecting robot demos in the wild is hard! Presenting DexWild 🙌🏕️ Human data collection system that works in diverse environments, without robots 💪🦾 Human + Robot Cotraining pipeline that unlocks generalization 🧵👇

Training robots for the open world needs diverse data But collecting robot demos in the wild is hard! Presenting DexWild 🙌🏕️ Human data collection system that works in diverse environments, without robots 💪🦾 Human + Robot Cotraining pipeline that unlocks generalization 🧵👇

Tony Tao

97,762 次观看 • 1 年前

1/5 🚀 Thrilled to open-source OSCAR 🤖 — an action-conditioned world model for robotics, led by the visiting student in my group Zhuoyuan Wu! It generalizes across different robot embodiments with precise action controllability. All trained on a single GH200 GPU, and outperforms existing open-sourced baselines, which have larger model capacity and need more compute. Everything is public, including training data. 📄 Paper: 🌐 Project: 💻 Code: 🤗 Robot data: 🤗 Human data: 🤗 Weights: #Robotics #WorldModels #AI #OpenSource

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Jun Gao

105,237 次观看 • 4 个月前

Human Data. Robot Data. Virtual Data. BrainCo Dexterous Data Matrix connects diverse data sources to establish a closed-loop data ecosystem, enabling robots to learn from real-world experiences and achieve more natural interactions. #BrainCo #EmbodiedAI #FutureRobotics

Human Data. Robot Data. Virtual Data. BrainCo Dexterous Data Matrix connects diverse data sources to establish a closed-loop data ecosystem, enabling robots to learn from real-world experiences and achieve more natural interactions. #BrainCo #EmbodiedAI #FutureRobotics

Tulsi Soni

67,586 次观看 • 2 个月前