RaySt3R was accepted to NeurIPS! Check out the HuggingFace demo for image to 3D in cluttered scenes huggingface.co/spaces/bartd...
In "hearing the slide"👂 (led by @yuemin-mao.bsky.social ) we estimate *loss* of contact with a contact microphone, and use it to learn dynamic constraints.⚡ It allows moving multiple intricate objects🍷 efficiently, even objects that would otherwise be hard to grasp. fast-non-prehensile.github.io
For which the code is also available github.com/naver/pow3r
Thanks Christian for the advertisement.
github link: github.com/naver/dune
🤖📦 Want to move many items FAST with your robot? Use a tray. But at high speeds, objects may fall off 💥.
Introducing our new method: it hears sliding 🎧, learns dynamic friction 🥌, and plans time-optimized motions to transport objects 🚀.
fast-non-prehensile.github.io/
🧵1/7
Imagine if robots could fill in the blanks in cluttered scenes.
✨ Enter RaySt3R: a single masked RGB-D image in, complete 3D out.
It infers depth, object masks, and confidence for novel views, and merges the predictions into a single point cloud. rayst3r.github.io
