📢 FLAIR-HUB dataset A new large-scale, multimodal dataset for land cover and crop type mapping 🤗 Dataset: huggingface.co/datasets/IGN... 📄 Preprint: arxiv.org/abs/2506.07080 🤗 Pretrained models: huggingface.co/collections/... 💻 Code: github.com/IGNF/FLAIR-HUB 🌐 Project : arxiv.org/abs/2506.07080

FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping

The growing availability of high-quality Earth Observation (EO) data enables accurate global land cover and crop type monitoring. However, the volume and heterogeneity of these datasets pose major pro...

arxiv.org

#CVPR2025 Sat June 14 (PM) 🌍 Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation @nicolasdufour.bsky.social @vickykalogeiton.bsky.social @davidpicard.bsky.social @loicland.bsky.social 📄 pdf: arxiv.org/abs/2412.06781 🌐 webpage: nicolas-dufour.github.io/plonk.html

AnySat has been accepted as a ✨ highlight at #CVPR2025! See you in Nashville 🎉 We’ll also be presenting this work at: 📍 @egu.eu on 02/04 in Vienna 📍 @esa.int / NASA Workshop on Foundation Models on 05/04 in Rome

Imagine-ENPC@imagineenpc.bsky.social · last yr.

#CVPR2025 Sat June 14 (PM) ✨ Highlight 🛰️ AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities @gastruc.bsky.social @nicaogr.bsky.social @loicland.bsky.social 📄 pdf: arxiv.org/abs/2412.14123 🌐 webpage: gastruc.github.io/anysat

We're hiring! IMAGINE @ École des Ponts (Paris area) is opening a 4-year "CV for X" researcher position: – competitive salary – no teaching load – starting pkg ≈ 2 PhDs – goal: impactful core AI + X (climate, biodiversity, robotics...) Apply by May 31: imagine-lab.enpc.fr/wp-content/u...

🚨 Workshop alert! 🌍💿 TerraBytes: Towards global datasets and models for Earth Observation Co-located with ICML 2025 (Vancouver, Canada) 🔗 terrabytes-workshop.github.io 📝 We accept short 4-pages and full 8-pages paper on remote sensing, Earth Observation and machine learning. 📆 Deadline: May 16th

Fantastic idea from @davidpicard.bsky.social. All are welcome, even if you don't have a CVPR paper!

David Picard@davidpicard.eurosky.social · last yr.

🔥🔥🔥 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!

🚨 Future open positions in AI at my home institution* targeted towards young researchers. These are tenure track positions with a good starting package, aimed at guiding you towards an ERC StG within 4 years. Feel free to contact me in DM. *ENPC, part of Institut Polytechnique de Paris

Our CVPR Workshop EarthVision, bridging computer vision and Earth observation, was accepted at #CVPR2025 for its 8th edition! Submit your papers by March 3 and stay tuned for more info : grss-ieee.org/events/earth...

Check out our new work with @gastruc.bsky.social and @nicaogr.bsky.social and Clément Mallet! The one-stop shop for multimodal Earth Observation 🤩

Guillaume Astruc@gastruc.bsky.social · 2y ago

🤔 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:

Amazing work again by @nicolasdufour.bsky.social, check out the demo with any picture and see if our model can guess its location! 🔗 huggingface.co/spaces/nicol...

Nicolas Dufour@nicolasdufour.bsky.social · 2y ago

🌍 Guessing where an image was taken is a hard, and often ambiguous problem. Introducing diffusion-based geolocation—we predict global locations by refining random guesses into trajectories across the Earth's surface! 🗺️ Paper, code, and demo: nicolas-dufour.github.io/plonk

Airborne #LiDAR has revolutionized the study of ancient rainforest civilizations by seeing through dense canopies. Yet archaeologists still annotate their data manually. Introducing Archaeoscape at #NeurIPS2024 —the first deep learning-scale, open-access archaeological dataset🧵👇

Anne Gagneux, Ségolène Martin, @quentinbertrand.bsky.social Remi Emonet and I wrote a tutorial blog post on flow matching: dl.heeere.com/conditional-... with lots of illustrations and intuition! We got this idea after their cool work on improving Plug and Play with FM: arxiv.org/abs/2410.02423