I’ll be at #SIGGRAPHAsia2025 next week presenting our paper MILo! Join the Neural Fields and Surface Reconstruction session on Tuesday, December 16. If you’ll be in Hong Kong and would like to discuss research, or grab a coffee ☕️ feel free to reach out.

We introduce MIRO: a new paradigm for T2I model alignment integrating reward conditioning into pretraining, eliminating the need for separate fine-tuning/RL stages. This single-stage approach offers unprecedented efficiency and control. - 19x faster convergence ⚡ - 370x less FLOPS than FLUX-dev 📉

Familiar names among #ICCV2025 Outstanding Reviewers from our team 😇 Antoine Guédon @antoine-guedon.bsky.social Sinisa Stekovic Renaud Marlet 👏 @iccv.bsky.social iccv.thecvf.com/Conferences/...

1/n🚀Gaussians > Differentiable function > Mesh? Check out our new work: MILo: Mesh-In-the-Loop Gaussian Splatting! 🎉Accepted to SIGGRAPH Asia 2025 (TOG) MILo is a novel differentiable framework that extracts meshes directly from Gaussian parameters during training. 🧵👇

I'm at #CVPR2025 to present our paper 🍵MAtCha Gaussians🍵, today Friday afternoon, Hall D, Poster 53! If you're in Nashville and want to discuss detailed 3D mesh reconstruction from sparse or dense RGB images, let's connect! @kyotovision.bsky.social

Behind every great conference is a team of dedicated reviewers. Congratulations to this year’s #CVPR2025 Outstanding Reviewers! cvpr.thecvf.com/Conferences/...

#CVPR2025 Fri June 13 (PM) ✨ Highlight 🍵 MAtCha Gaussians: Atlas of Charts for High-Quality Geometry and Photorealism From Sparse Views @antoine-guedon.bsky.social @kyotovision.bsky.social 📄 pdf: arxiv.org/abs/2412.06767 🌐 webpage: anttwo.github.io/matcha/

💻We've released the code for our #CVPR2025 paper MAtCha! 🍵MAtCha reconstructs sharp, accurate and scalable meshes of both foreground AND background from just a few unposed images (eg 3 to 10 images)... ...While also working with dense-view datasets (hundreds of images)!

🔥🔥🔥 CV Folks, I have some news! We're organizing a 1-day meeting in center Paris on June 6th before CVPR called CVPR@Paris (similar as NeurIPS@Paris) 🥐🍾🥖🍷 Registration is open (it's free) with priority given to authors of accepted papers: cvprinparis.github.io/CVPR2025InPa... Big 🧵👇 with details!

Starter pack including some of the lab members: go.bsky.app/QK8j87w

1/13 🐊 Introducing our latest work on improving relative camera pose regression with a novel pre-training approach Alligat0R (arxiv.org/abs/2503.07561)! @gbourmaud.bsky.social @vincentlepetit.bsky.social

🤔 What if embedding multimodal EO data was as easy as using a ResNet on images? Introducing AnySat: one model for any resolution (0.2m–250m), scale (0.3–2600 hectares), and modalities (choose from 11 sensors & time series)! Try it with just a few lines of code:

⚠️Reconstructing sharp 3D meshes from a few unposed images is a hard and ambiguous problem. ☑️With MAtCha, we leverage a pretrained depth model to recover sharp meshes from sparse views including both foreground and background, within mins!🧵 🌐Webpage: anttwo.github.io/matcha/

MAtCha Gaussians: Atlas of Charts for High-Quality Geometry and Photorealism From Sparse Views @antoine-guedon.bsky.social, Tomoki Ichikawa, Kohei Yamashita, Ko Nishino tl;dr: underlying scene geometry mesh->an Atlas of Charts->render with 2D Gaussian surfels arxiv.org/abs/2412.06767

Welcome to all the newcomers! Here's a starter pack for the 3D Computer Vision community: go.bsky.app/Cfm9XFe