Daniel Duckworth @duck
Research Scientist at Google DeepMind, Berlin. https://t.co/FNRtZRR38w stronglyconvex.com Berlin, DE Joined September 2010-
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I had the pleasure last month of giving slightly provocative talk at Bliss AI, a a wonderful student-run organization here in Berlin. The best part: the talk is online for everyOne to enjoy! Behold: "NeRF is dead" youtu.be/FtaC5lh8hxs?si…
Are you at #SIGGRAPH2024 and want to learn how to reconstruct meshes from multi-view images that contain details like individual strands of grass? Then come today to the "Radiance Field Processing" session at 2 p.m. in Mile High 1. binary-opacity-grid.github.io
InterNeRF: Scaling Radiance Fields via Parameter Interpolation @clintonjwang, @PeterHedman3, Polina Golland, @jon_barron, @duck tl;dr: use camera origin to assign camera region to partitioned parameter grid and compute bilinear interpolation weights arxiv.org/pdf/2406.11737
Googleがリアルタイムに高精度なレンダリングを実現する新技術「SMERF」を発表 gigazine.net/news/20231214-…
@dariel_noel @LinusEkenstam You'll have to read the paper for all of the technical details, but in short: clever use of OpenGL texture lookups + lots of model training magic.
Seeing the amazing new SMERF technology immediately made me imagine a time when we can walk around in environments like this, styled to be anything we can imagine. All happening in realtime, shaped with voice prompts or virtual paint or sculpt marks. Here's a test of using some of the SMERF demo scenes to drive a generative AI image stream in Krea.. incredible! It's like seeing the world through a new camera lens of imagination. I'll post a link to the incredible SMERF paper by @duck and his colleagues below.. what a time to be alive! #ai #art
@MartinNebelong This is absolutely wild! The future is now.
@Mi_Niemeyer I couldn't have done it without all of my amazing collaborators, especially co-first author @PeterHedman3!
@RadianceFields Want to learn more? Check out my OG explainer thread!
Introducing SMERF: a streamable, memory-efficient method for real-time exploration of large, multi-room scenes on everyday devices. Our method brings the realism of Zip-NeRF to your phone or laptop! Project page: smerf-3d.github.io ArXiv: arxiv.org/abs/2312.07541 (1/n)
@supremebeme @RadianceFields This and other large scenes are captured with a DSLR camera and a fisheye lens. Approximately ~1500 photos are used. Capture takes 30~60 min.
@AISavvyKushan Not just DeepMind! This wouldn't have been possible without my amazing colleagues in Google Research, Google Inc, and Tübingen.
@Kyrannio Don't forget my amazing collaborators at Google Research, Google Inc, and Tübingen! This was very much a team effort. More info here:
Introducing SMERF: a streamable, memory-efficient method for real-time exploration of large, multi-room scenes on everyday devices. Our method brings the realism of Zip-NeRF to your phone or laptop! Project page: smerf-3d.github.io ArXiv: arxiv.org/abs/2312.07541 (1/n)
@Royal790721 @wholemars No GSplats were harmed in the making of SMERF :)
@wholemars Want to learn more? Check out my OG explainer thread:
Introducing SMERF: a streamable, memory-efficient method for real-time exploration of large, multi-room scenes on everyday devices. Our method brings the realism of Zip-NeRF to your phone or laptop! Project page: smerf-3d.github.io ArXiv: arxiv.org/abs/2312.07541 (1/n)
@gkopanas Thanks for the kind words, Georgios! I look forward to the next generation of 3DGS work as well. It's just a matter of time till 3D capture & presentation is accessible as 2D is today.
@cpheinrich @Google The renderer is already open source! Entry point is here: github.com/smerf-3d/smerf…
Thoughts NeRFs were dead? Google DeepMind just dropped SMERF — streamable, multi-room NeRFs with cm-level detail. Oh and it works realtime on mobile 🤯 It’s a sweet spot between the speed of Gaussian Splatting and the quality of Zip-NeRF. More below ⬇️
@Snosixtytwo Thank you, Bernhard :). It's an honor to hear it from you!
@RadianceFields Big thanks to @RadianceFields for the quick write-up! Fantastic work :)
SMERF from Google Research (again) achieves Zip-NeRF quality, operating at a remarkable 60fps on everyday devices like smartphones and laptops. 🔗 neuralradiancefields.io/the-merf-that-…
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