<img src="https://ml.globenewswire.com/Resource/Download/5369eea8-ba95-471a-91b5-853e0e17c212?size=2" nborder="0" align="left" hspace="5" vspace="5" title="NR-logo.png" alt="Noitom Robotics"/>Available now on Hugging Face as the first public dataset of the company’s World Compiler approach Key facts <ul type="disc"><li style="margin-bottom:1.7pt;">Noitom Robotics has publicly released HiPHI: 617.5 hours of high-precision human motion and object interaction from 132 performers, captured at sub-millimeter precision — among the largest datasets of its kind ever made publicly available.</li><li style="margin-bottom:1.7pt;">Built for embodied and physical AI: policies trained on HiPHI run on a physical Unitree G1 humanoid — running, sitting, crawling, carrying a box, and pulling a suitcase — with the same foundation serving humanoid learning, digital humans, and computer graphics.</li><li style="margin-bottom:6pt;">Available now at huggingface.co/datasets/noitomrobotics/HiPHI, free for the research community; commercial licensing via modalitynet.com. </li></ul> BEIJING, Aug. 20, 2026 <a href="https://www.globenewswire.com" target="_blank">(GLOBE NEWSWIRE)</a> -- <a href="https://www.globenewswire.com/Tracker?data=RcFK3YhokGjpT1ufCeNxn7EH942_Jl-Vk-P63ZQHbG4u7cO7i5bt95VgMGY4lVACp-Lw3LvRHS_eAnwme0wpojkXGkfPQUWlc23YQUQbdS8=" rel="nofollow" target="_blank" title="Noitom Robotics">Noitom Robotics</a> (NR) today released <a href="https://www.globenewswire.com/Tracker?data=LjfJ-v4R0HmZbIaws93Kdh1EoPxI5a1f6AhP0mpm3W8f8GbA3qjAok_FMsHyeuGIbdh6T6GxeoQaYfrEueQN_0nfxROpcK81bf4gSHdIQ3w=" rel="nofollow" target="_blank" title="HiPHI">HiPHI</a> (pronounced “hi-fi”), a high-precision optical motion-capture dataset for researchers and engineers working on humanoid learning, digital humans, and computer graphics, at the <a href="https://www.globenewswire.com/Tracker?data=vJouoEPM_qvv5uyb621bgHZk0XEzQ3JosPoHrN4A8V7s1ELgdXCvm8loYZEQPs-WHt4cYwtDld_Xtyeh1tE3zZJGHiWMhzZWPl7bWhu5orkG-IQEOOtHp-IJHrCjaAGf" rel="nofollow" target="_blank" title="World Robot Conference">World Robot Conference</a> in Beijing. The dataset is publicly available now on Hugging Face, and is the first the company has made public under its <a href="https://www.globenewswire.com/Tracker?data=vJouoEPM_qvv5uyb621bgHD6eiI47riIJKgcsfLTU5A8QO3TpA8nTxyCuNDX1OM_VAeCqJ-krW2upGdNfQ7xzy0fGzvv3k-cBwjy78B373g=" rel="nofollow" target="_blank" title="World Compiler">World Compiler</a> approach: making the physical world learnable for AI systems. <a data-type="gnw-snippetgallery" href="https://www.globenewswire.com/Tracker?data=MLGuhvoxcMIO4NHAMXpNafbT1E7Iw4pHRdH5QDiO3os8_Vdjf1FNe3YtewY5RG_U6851-67WOXv9e7_jPtLRQW6RIg3AphECn9cdQK5jXW8=" rel="nofollow" target="_blank"><img alt="HiPHI Media Library: HiPHI diagrams and figures." data-mce-style="display: block; margin-left: auto; margin-right: auto;" src="https://ml.globenewswire.com/Resource/Download/45ef2182-543f-41dd-9933-337431243630/" style="display:block; margin-left:auto; margin-right:auto;" data-dpi="0" data-caption="HiPHI: A Large-Scale Benchmark for High-Precision Human Motion and Object-Interaction" data-filename="1219372981"></a> <a href="https://www.globenewswire.com/Tracker?data=brLk0gaw1ZGhJcPvqDI1g4fmhj_ML7IalPcc-1lSD12VIm7dkKkVJ15VEydDKiDGQljCgy4sHcplWnkbJzCtmHAvQOEgK3SOzNpZQNWxiCzfDZqgck49hs8KcIL68yOPnZXR6dVacADYHVl06uIzx9AMXDGo-Qtth-kkxM5Yw6uZK4XUtA8P696SawxEXomPcsdZ2dQEWpkZAIc0RTnKx6fdj4-Ko7lP0TR5sbEiw20=" rel="nofollow" target="_blank" title="A Media Snippet accompanying this announcement is available by clicking on this link.">A Media Snippet accompanying this announcement is available by clicking on this link.</a> The release totals 617.5 hours of motion, including left-right mirrored counterparts: 371.8 hours of whole-body human motion and 245.7 hours of human-object interaction in which each object’s trajectory and mesh are recorded in sync with the performer. The data was captured from 132 performers at 90 Hz with sub-millimeter marker tracking, and is organized around motion units drawn from FrameNet, a linguistic framework organizing human action semantics. It ships with its documentation in full: an <a href="https://www.globenewswire.com/Tracker?data=LZJnpZEWIjbXjU2XTZk0enYxbRRq65bBKK6kLa4QNlYzKgr9wSNA83IM1RJgct92GDIiEzrzMStZkc2SUZzo4PVcSGa2hrmMVRYTsl4iDv4=" rel="nofollow" target="_blank" title="academic paper">academic paper</a> — written by the NR research team — reporting the broadest measured motion coverage and the lowest per-frame physical-quality error values among the datasets compared, together with published quality metrics and a written evaluation guide. Policies trained on HiPHI run on a physical Unitree G1 humanoid: running, sitting, crawling, carrying a box, and pulling a suitcase. “The bottleneck in physical AI is not how much data exists, but how much of it a machine can actually learn from,” said Dr. Tristan Ruoli Dai, Founder and CEO of Noitom Robotics. “HiPHI is our first answer: coverage designed before a single frame was captured, precision that survives the transfer to real robots, and the objects people touch recorded as part of the motion itself. Data like this is usually a company’s most closely guarded asset. We are making it public because embodied intelligence needs a shared foundation it can trust — and because our infrastructure keeps producing more.” Datasets of this kind are scarce. The field has long faced a trade-off: internet-scale video lacks the precise physical states and interaction grounding robots need, while high-fidelity laboratory datasets cover only narrow slices of behavior — and high-precision capture is slow and costly to produce, so what exists is typically held as a proprietary asset. Public releases at this scale and precision are rare, and rarer still from a commercial data producer. To the company’s knowledge, HiPHI is among the largest high-precision human-motion datasets ever made publicly available. For researchers, HiPHI provides a physically grounded foundation for humanoid tracking, imitation learning, motion generation, and motion-space analysis — a foundation that extends to motion-prior models for digital humans and computer graphics. For companies building physical AI systems, the public release also serves as a reference: full-depth access to the data the company produces continuously for commercial partners. “Coverage, per-frame quality, and object state decide whether a humanoid can actually learn from motion data — so those are the things we designed for, measured, and published,” said Dr. Lei Han, Chief of Research and Development at Noitom Robotics. “Everything a researcher needs is in the release: standardized BVH, synchronized object trajectories, a semantic motion index, and the evaluation guide. Anyone can download it today and hold our numbers to the light. And it is a faithful sample of what our infrastructure produces — more than 100,000 hours a year — for our partners.” HiPHI is available now on <a href="https://www.globenewswire.com/Tracker?data=iiziu_7VrnLTpMmnzVmbWUKaZ7QfjlOLEH220whevcJWLxoQvhSmZLT9bNRjfQMabvI0mdVlznFKJZCn7rO39Mcxy5YUhH2ZsTr3sUhd-XTj_4Bu2KeKzckzplwQLhjl" rel="nofollow" target="_blank" title="Hugging Face">Hugging Face</a>, free of charge for the research community under the ModalityNet Open Research License; commercial licensing is available through modalitynet.com. Noitom Robotics continues its launch activities at RO-MAN 2026 in Fukuoka (24–28 August), and plans further public releases, beginning with an omni-modality interaction corpus later this year. Upcoming releases will add support for widely used formats such as SMPL and SOMA. About Noitom Robotics Noitom Robotics is a data company specializing in omnimodal data for Physical AI. Through ModalityNet (modalitynet.com) — our implementation of the World Compiler — we transform real-world human motion, interaction, and behavior into learnable representations across three corpora: HiPHI-MOV (motion), HiPHI-OM (omni-modal interaction), and ITW (in-the-wild), giving embodied AI the structured, training-ready foundation that raw data alone cannot provide. Media contacts — International: Tan Evan, evan@noitomrobotics.com. <img alt="" src='https://ml.globenewswire.com/media/YmFmOTVmMzktZDZmYS00NjE0LTlkNDYtNzFmNTNmY2Q0MzU3LTEzMjM3OTktMjAyNi0wOC0yMC1lbg==/tiny/Noitom-Robotics.png' referrerpolicy='no-referrer-when-downgrade' />

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Noitom Robotics Releases HiPHI, One of the Largest High-Precision Human Motion Datasets Ever Made Public, at the World Robot Conference

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