Tired of designing task rewards? New work, PhysHOI, enable simulated humanoid to learn diverse basketball skills 🏀 purely from human demonstrations. Code available now! Site: https://t.co/LL2QIJV6VM Paper: https://t.co/kWFmsi0cSa Code/Data: https://t.co/B1bya43D10

First-ever real-world basketball demo by a humanoid robot 🤖🏀 Bonus: I became the first person to record a block against a humanoid🤭 #Robotics #AI #TechDemo #NBA

🔥 #CVPR2025 Highlight Paper 🔥 Join us at Hall D #166! 📅 July 14, 5-7 PM 💬 Let's discuss Humanoid Skill Learning! 📜 Paper: “SkillMimic: Learning Basketball Interaction Skills from Demonstrations” 🏀 Project Page: https://t.co/23Ir3d8IVO 💻 Code/Data: https://t.co/nW1v2k9kNn

Ever seen a humanoid robot serve beer without spilling a drop? Now you have. 🍻 Introducing Hold My Beer: learning gentle locomotion + stable end-effector control.

Who can stop this guy🤭? Highly robust basketball skills powered by our #SIGGRAPH2025 work Project page: https://t.co/v38eGgwxvb There are more cases for enhancing general interaction and locomotion skills!

Trapped by data quality and volume challenges in imitation learning? Check our #SIGGRAPH2025 paper: 🤖SkillMimic-V2: Learning Robust and Generalizable Interaction Skills from Sparse and Noisy Demonstrations. 🌐 Page： https://t.co/tK6JhgD5MK 🧑🏻‍💻 Code： https://t.co/fhnKZwwcLD

Excited to share our latest work! 🤩 Masked Mimic 🥷: Unified Physics-Based Character Control Through Masked Motion Inpainting Project page: https://t.co/CbnEEs4NAv with: Yunrong (Kelly) Guo, @ofirnabati, @GalChechik and @xbpeng4. @SIGGRAPHAsia (ACM TOG). 1/ Read

WoCoCo is accepted by #CoRL2024. Codes will be released weeks later. (Complaint: 2 of 3 reviewers raised 90% of the questions and did not join the rebuttal. I feel it like an ICRA submission with long delayed notification. We have revised our manuscript accordingly tho.)

#CVPR2024 #HandObjectInteraction Excited to share our dataset TACO - the first large-scale real-world 4D bimanual tool usage dataset covering diverse Tool🥄-ACtion🙌-Object🍵 compositions and object geometries. Join us at Poster 213, Arch 4A-E, Fri 10:30am - noon PDT🍺.

From learning individual skills to composing them into a basketball-playing agent via hierarchical RL -- introducing SkillMimic, Learning Reusable Basketball Skills from Demonstrations 🌐: https://t.co/E2dSADhjE9 📜: https://t.co/DQXEljVOmO 🧑🏻‍💻: https://t.co/XKqAJOizb1 Work led

 🤖Introducing 📺𝗢𝗽𝗲𝗻-𝗧𝗲𝗹𝗲𝗩𝗶𝘀𝗶𝗼𝗻: a web-based teleoperation software!  🌐Open source, cross-platform (VisionPro & Quest) with real-time stereo vision feedback.  🕹️Easy-to-use hand, wrist, head pose streaming. Code:  https://t.co/3lu5ZTMNfA

It took my brain a while to parse what's going on in this video. We are so obsessed with "human-level" robotics that we forget it is just an artificial ceiling. Why don't we make a new species superhuman from day one? Boston Dynamics has once again reinvented itself. Gradually,

🤔 Ever wondered if simulation-based animation/avatar learnings can be applied to real humanoid in real-time? 🤖 Introducing H2O (Human2HumanOid): - 🧠 An RL-based human-to-humanoid real-time whole-body teleoperation framework - 💃 Scalable retargeting and training using large

This is how ALOHA's "teleoperation" system works - a fancy word for "remote control". Training robots will be more and more like playing games in the physical world. A human operates a "joystick++" to perform tasks and collect data, or intervene if there's any safety concern.

Coming to PHC in 2024 -- hands!

Figure-01 has learned to make coffee ☕️ Our AI learned this after watching humans make coffee This is end-to-end AI: our neural networks are taking video in, trajectories out Join us to train our robot fleet: https://t.co/egQy3iz3Ky https://t.co/Y0ksEoHZsW

You can now ask your simulated humanoid to perform actions, in REAL-TIME 👇🏻 Powered by the amazing EMDM (@frankzydou, @Alex_wangjingbo, etal) and PHC. EMDM: https://t.co/USGcRmhssX PHC: https://t.co/wOxdY1i24f Simulation: Isaac Gym

Interested in image restoration? Check our #ICLR2023 spotlight paper "Zero Shot Image Restoration Using Denoising Diffusion Null-Space Model" for a brand new perspective! 👻 https://t.co/qqSRGkSJJY https://t.co/ScAOz93jtB

DDNM is a zero-shot image restoration model. It decomposes data space into the range/null space of the linear degradation operator and then refines an image in null space only to ensure data consistency while improving realness.