My fav use of ChatGPT + Browsing so far 🤩 Looking through the code for the Twitter algorithm and asking questions, seeing how things work, what means what etc. I can't code so i can't read the repos

Helsing is hiring 2024 PhD interns in the area of 3D computer vision, machine learning, and generative AI. See intern call below for more details. helsing.ai/jobs/4264969101

Super excited to announce that our workshop ViLMa - Visual Localization and Mapping has been accepted at #CVPR2026. Please stay tuned for more updates & see you all in Seattle!

The GOAT of tennis Novak Djokovic said: "35 is the new 25.” I say: “60 is the new 35.” AI research has kept me strong and healthy. AI could work wonders for you, too!

Lecture recordings from MIT about inverse rendering. Teaches also some Gaussian Splatting basics for free! scenerepresentations.org/courses/invers… Credits go to Manan Shah for bringing it to my attention #3DGS

With satellite imagery, it’s hard to get labels. Solution? DINOv2! WRI+Meta trained a satellite DINOv2 for tree height estimation. They created an interactive map of tree height of the whole globe (!) at 1-meter res (!): …toring-okw37.projects.earthengine.app/view/canopyhei… Quizz: Can you recognize this city?

Make sure to join us for the Visual Localization and Mapping Workshop (ViLMa) on Monday morning #CVPR2026! We have an outstanding lineup of keynote speakers: Sebastian Scherer Lukas von Stumberg VincentLepetit Jakob Engel Peter Kontschieder Laura Leal-Taixe Marc Pollefeys More details: vilma-workshop.github.io

What a great community. We had a full house yesterday and a great lineup of keynote speakers! We had stimulating discussions and a really exciting panel! We hope everyone enjoyed it! Thanks to all the speakers and to the organizers who contributed to the success of the event!

🚀 Excited to release OpenVPRLab! 🎉 An open-source framework for Visual Place Recognition (VPR), featuring extensible, modular, and scalable components, enabling researchers to train/develop deep VPR models with reproducible SOTA performance. 🔗github.com/amaralibey/Ope… 🧵👇

very cool to see a pretty exhaustive and extensive technical report on llama-3.1! a few fun snippets 🧵

Mark Zuckerberg on Meta's open source AI strategy: "We're not doing this because we're altruistic... I don't view it as giving it away, I view it as you guys all making it better for me"

I’ll be at the conference tomorrow and on Friday. PM me if you’d like to chat about what we are doing!

Devil's advocate mode on: Navigation World Models have existed for a long time... they're called maps! And there are plenty of good algorithms out there which enable robots to build them / render views from them / localise within them / use them for planning. #SLAM #SpatialAI :)

Introducing MASt3R-SLAM, the first real-time monocular dense SLAM with MASt3R as a foundation. Easy to use like DUSt3R/MASt3R, from an uncalibrated RGB video it recovers accurate, globally consistent poses & a dense map. With Eric Dexheimer*, Andrew Davison (*Equal Contribution)

We’ve had fun testing the limits of MASt3R-SLAM on in-the-wild videos. Here’s the drone video of a Minnesota bowling alley that we’ve always wanted to reconstruct! Different scene scales, dynamic objects, specular surfaces, and fast motion.

One reason generative 3D is hard is that the world has barely any 3D training data. Today, most humans on earth will snap a few photos and write paragraphs of text. In contrast, earth has maybe ~50k 3D artists, and each will make maybe ~1k photoreal 3D models over their career.

"Building Rome with Convex Optimization" has been accepted to #RSS2025! Try XM, our new structure from motion pipeline powered by GPU-accelerated convex semidefinite optimization: github.com/ComputationalR… XM solves large-scale (nonconvex) global bundle adjustment problem via

Unanswered research questions in Image Matching