Joined October 2023
It's time to scale!
Introducing Light-O1, a whole-body intelligence model scaled through human action pretraining. • Human action at scale: We learn from structured human actions recovered from internet videos, capturing a scale and diversity that robot data collection alone struggles to match. • Cross-embodiment transfer scaling law: Scaling human action pretraining yields power-law reductions in prediction error across embodiments. • Whole-body intelligence: Adapted to different humanoids, Light-O1 coordinates movement, posture, and manipulation to autonomously perform household tasks.
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Autonomous. By Light Origins. Stay tuned.
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Our humanoid robot vaults, climbs, and crosses terrain it’s never seen before—deciding which move to use in real time, completely on its own 🤖 Real → sim → real. 👇
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🚨 We just released 🎞️MoVieS — a feed-forward model that reconstructs 4D scenes in ⚡️1 second My favorite part: It learns dense (pixel-wise) sharp 3D world movements from novel view rendering + sparse point tracking supervision 🤯🎯 Check it out 👉 chenguolin.github.io/project…
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📢I'm pleased to introduce GlueStick: A robust image matcher that combines points and lines📢 ➡️Website: iago-suarez.com/gluestick ➡️Code: github.com/cvg/GlueStick ➡️Paper: arxiv.org/pdf/2304.02008.pdf This is a collaboration with Rémi Pautrat, Yifan Yu, @mapo1 and @visionviktor. 1/🧵
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3D Line Mapping Revisited @B1ueber2y, Yifan Yu, Rémi Pautrat, @mapo1 , @visionviktor tl;dr: Point-guided line SfM with scale-invariant scoring -> profit. Even improves SuperPoint + Colmap bundle adjustment arxiv.org/abs/2303.17504.pdf
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