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Very impressive results!

We just finished a joint code release for CamP (camp-nerf.github.io) and Zip-NeRF (jonbarron.info/zipnerf/). As far as I know, this code is SOTA in terms of image quality (but not speed) among all the radiance field techniques out there. Have fun! github.com/jonbarron/camp…

📢📢📢 A pulse of light takes ~3ns to pass through a Coke bottle—100 million times less than it takes you to blink. Our work lets you fly around this 3D scene at the speed of light, revealing propagating wavefronts of light that are invisible to the naked eye—from any viewpoint!

Excited to share our work on image-to-3D scene generation: cat3d.github.io CAT3D uses a multi-view diffusion model to generate novel views, and just inputs these to NeRF/3DGS. Create anything in 3D in 1 minute!

IllumiNeRF enables relighting without expensive inverse rendering. We use a diffusion model trained to relight a single image, and turn its samples into a consistent 3D relit NeRF. With Xiaoming Zhao (currently on the job market!) Pratul Srinivasan Keunhong Park Ricardo Martin-Brualla Philipp Henzler

I'm going to present our work at the oral session tomorrow (Wednesday), 9am at #CVPR2024. Come check it out and hang out at the poster session (ours is number 399) immediately after!

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

📣 Dr. Dor Verbin from Google DeepMind will give a Zoom seminar at Purdue on Tuesday, Sep 17, at 10 AM ET! See the flyer for more information. DM me or Stanley H. Chan for the Zoom link. PurdueECE IEEE Computational Imaging TC

(1/N) Flash Cache: Reducing Bias in Radiance Cache Based Inverse Rendering Website: benattal.github.io/flash-cache/ tl;dr our #ECCV2024 (oral ✨) paper presents a new system for inverse rendering that is more physically accurate, and therefore less biased, than existing approaches.

Our new paper performs exact volume rendering at 30FPS@720p, giving us the highest detail 3D-consistent NeRF! Paper: arxiv.org/abs/2410.01804 Website: half-potato.gitlab.io/posts/ever

Our team is looking for interns! If you're interested in working with us next summer, please apply.

🚀 Introducing SimVS: our new method that simplifies 3D capture! 🎯 3D reconstruction assumes consistency—no dynamics or lighting changes—but reality constantly breaks this assumption. ✨ SimVS takes a set of inconsistent images and makes them consistent with a chosen frame.

The code for EVER: Exact Volumetric Ellipsoid Rendering has finally been released! To recap our paper, EVER is an exact, real-time volume rendering method, capable of achieving the highest quality results on large scenes! Code: github.com/half-potato/ev…

We're running a workshop on physics-inspired 3D vision and imaging at CVPR this year! We'll have a poster session, so if you'd like to present something, please submit your work by the April deadline. Otherwise, just come hang out with us at the workshop! pi3dvi.github.io