Dynamic 3D Gaussian Fields for Urban Areas Tobias Fischer, Jonas Kulhanek, Samuel Rota Bulò, Lorenzo Porzi, Marc Pollefeys, Peter Kontschieder tl;dr: 3D Gaussian primitives->geometry scaffold; neural fields->appearance; scene graph->scene dynamics arxiv.org/pdf/2406.03175

Excited to announce 🚀gsplat v1.0🚀: a ⏩efficient⏩ CUDA backend for 3D Gaussian Splatting! docs.gsplat.studio A drop-in replacement of the official impl. with: - Up to 2x faster training; - Up to 4x less GPU memory; - Render millions of GSs in real-time; - And more;

I wrote this useful Python script to prepare your paper (arXiv) submissions. It crops and resizes all images to fit a specified DPI, removes all comments, removes unused files, and generates a zip file that can be directly uploaded. gist.github.com/jkulhanek/b48f…

WildGaussians 3D Gaussian Splatting in the Wild While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both

WildGaussians: 3D Gaussian Splatting in the Wild arxiv.org/abs/2407.08447 Project: wild-gaussians.github.io Code: github.com/jkulhanek/wild… Method ⬇️ 1 I 2

🚀 Ready to take 3D reconstruction to the next level? Whether you're working on NeRF or 3DGS, our new method, GLOMAP, is here to impress! 🌟 It's faster and more accurate than COLMAP on several datasets. 🌐 Website: lpanaf.github.io/eccv24_glomap/ Marc Pollefeys, Linfei Pan, J. Schönberger

Thanks a lot for sharing!

EdgeGaussians - 3D Edge Mapping via Gaussian Splatting Kunal Chelani, Assia Benbihi, Torsten Sattler, Fredrik Kahl tl;dr: explicit representation of the 3D edge points; 3D edge point->center of a 3D Gaussian; edge direction->principal axis of the Gaussian arxiv.org/pdf/2409.12886

Meta 3D AssetGen has been accepted to #neurips2024!! assetgen.github.io Big congrats to the team Roman Shapovalov, David Novotny, Andrea Vedaldi, Filippos Kokkinos, Tom Monnier, Mahendra Kariya, Natalia Neverova and everyone involved! :)

Happy to share that our paper was accepted as spotlight NeurIPS Conference 2024! See you in Vancouver 🇨🇦

Our WildGaussians paper got accepted to NeurIPS Conference 2024 🎉!

Heads up! Mosaic dropped a pretty wild dataset of 1.26 million 360° images of Prague 🤯 If you're a researcher, creator or developer into 3D/AI/Geo, I think you're gonna wanna play with this Here's the scoop on this 15 TERAPIXEL dataset & the crazy things you can do with it 🧵

I’ll present our #NeurIPS2024 Spotlight Poster on Friday, 13 Dec 4:30-7:30pm PST in East Exhibit Hall A-C, booth #1505. Please step by to talk large-scale dynamic 3D Gaussians! :)

I will be presenting the WildGaussians paper this afternoon at NeurIPS Conference . To learn more about our paper, visit me at poster stand #1307 in East Exhibit Hall 16:30-19:30

We are releasing uCO3D! Built to supercharge 3D GenAI and digital-twin models, this evolution of CO3D features more and higher-quality object videos from 1k categories, 3D Gaussian Splats, and streamlined OSS tools. 💻Data&code: github.com/facebookresear… 📄Paper:

LODGE: Level-of-Detail Large-Scale Gaussian Splatting with Efficient Rendering Jonas Kulhanek, Marie-Julie Rakotosaona, Fabian Manhardt, Christina Tsalicoglou, Michael Niemeyer, Torsten Sattler, Songyou Peng, Federico Tombari tl;dr: camera distance->active Gaussians; pre-compute active

🚀 Just wrapped up my internship at Google with a paper submission! LODGE is a new large-scale level-of-detail 3DGS method, enabling efficient rendering even on mobile devices. Thanks to the amazing team at Google Zurich for making this possible! 📄lodge-gs.github.io

CL-Splats: Continual Learning of Gaussian Splatting with Local Optimization Jan Ackermann, Jonas Kulhanek, Shengqu Cai, Haofei Xu, Marc Pollefeys, Gordon Wetzstein, Leonidas Guibas, Songyou Peng tl;dr: DINOv2-based 2D binary change masks->voting+sampling->3D masks->3DGS-based local