🛰️ Introducing UniverSat: one transformer backbone for Earth Observation that handles ANY sensor, ANY spatial, spectral & temporal resolution, ANY scale — with a single set of weights. 🌍

What if you could turn any number of photos (3, 8, 15, or even 60) into one clean 3D surface (pts & mesh) with Flow Matching? Check out our new work, Surflo: Consistent 3D Surface Flow Model with Global State. 🧵 1/N 🔗https://anttwo.github.io/surflo/

🚀 DinoV3 just became the new go-to backbone for geoloc! It outperforms CLIP-like models (SigLip2, finetuned StreetCLIP)… and that’s shocking 🤯 Why? CLIP models have an innate advantage — they literally learn place names + images. DinoV3 doesn’t.

Some of our IMAGINE members at #CVPR2025

I am heartbroken that I am not at the conference, but seeing what the government is doing to its people and the world, I simply couldn't go there.

Looking forward to #CVPR2025! We will present the following papers:

This is an idea I've had for a while, but wow, it's working way better than expected! 🚀 The model looks really promising, even though it's just 256px for now.

Introducing Chapter-Llama #CVPR2025, a framework for 𝐯𝐢𝐝𝐞𝐨 𝐜𝐡𝐚𝐩𝐭𝐞𝐫𝐢𝐧𝐠 using Large Language Models! 🎬🦙 Check it out: 📄 Paper: arxiv.org/abs/2504.00072 🔗 Project: imagine.enpc.fr/~lucas.ventu... 💻 Code: github.com/lucas-ventur... 🤗 Demo: huggingface.co/spaces/lucas...

🔥🔥🔥 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

Introducing DaD, Part 2, a pretty cool keypoint detector.

Johan Edstedt@parskatt.bsky.social · last yr.

Introducing DaD (arxiv.org/abs/2503.07347), a pretty cool keypoint detector. As this will get pretty long, this will be two threads. The first will go into the RL part, and the second on the emergence and distillation.

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

Alligat0R: Pre-Training Through Co-Visibility Segmentation for Relative Camera Pose Regression @thibautloiseau.bsky.social, Guillaume Bourmaud, @vincentlepetit.bsky.social tl;dr: CroCo based; pixel in 1st image->co-visible or occluded or outside FOV in 2nd image arxiv.org/abs/2503.07561

🚨 News! 🚨 We have released the models from our latest paper "How far can we go with ImageNet for text-to-image generation?" Check out the models on HuggingFace: 🤗 huggingface.co/Lucasdegeorg... 📜 arxiv.org/abs/2502.21318

Lucasdegeorge/CAD-I · Hugging Face

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

David Picard@davidpicard.eurosky.social · 2y ago

🚨 New preprint! How far can we go with ImageNet for Text-to-Image generation? w. @arrijitghosh.bsky.social @lucasdegeorge.bsky.social @nicolasdufour.bsky.social @vickykalogeiton.bsky.social TL;DR: Train a text-to-image model using 1000 less data in 200 GPU hrs! 📜https://arxiv.org/abs/2502.21318 🧵👇

Check out our latest work on Text-to-Image generation! We've successfully trained a T2I model using only ImageNet data by leveraging captioning and data augmentation.

David Picard@davidpicard.eurosky.social · 2y ago

🚨 New preprint! How far can we go with ImageNet for Text-to-Image generation? w. @arrijitghosh.bsky.social @lucasdegeorge.bsky.social @nicolasdufour.bsky.social @vickykalogeiton.bsky.social TL;DR: Train a text-to-image model using 1000 less data in 200 GPU hrs! 📜https://arxiv.org/abs/2502.21318 🧵👇

🚨 New preprint! How far can we go with ImageNet for Text-to-Image generation? w. @arrijitghosh.bsky.social @lucasdegeorge.bsky.social @nicolasdufour.bsky.social @vickykalogeiton.bsky.social TL;DR: Train a text-to-image model using 1000 less data in 200 GPU hrs! 📜https://arxiv.org/abs/2502.21318 🧵👇

🧩 Excited to share our paper "RUBIK: A Structured Benchmark for Image Matching across Geometric Challenges" (arxiv.org/abs/2502.19955) accepted to #CVPR2025! We created a benchmark that systematically evaluates image matching methods across well-defined geometric difficulty levels. 🔍

🤔 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:

We @imagineenpc.bsky.social are slowly but surely entering our proposals for master's degree internships here: docs.google.com/document/d/1... These are 6 months projects that typically correspond to the end-of-study project in the French curriculum. Probably more offers to come, check it regularly.

2025 IMAGINE Internships

2025 Internship proposals at IMAGINE IMAGINE is a top research group on computer vision and machine learning. It is part of the LIGM lab and hosted at École des Ponts ParisTech (ENPC), about 25 min f...

docs.google.com