Congrats Dr. @vletzelter.bsky.social for his work defended in front of a stellar jury and answering to so many questions that @rflamary.bsky.social decided a break at some point ^^ Fun fact: Victor had not 4, not 6, but *8* advisors over the span of his thesis and he handled them brilliantly

Congrats to our @vletzelter.bsky.social for earning his PhD for his work on "Multiple Choice Learning from Ambiguous Signals". Victor is a resourceful, curious and kind researcher. Good luck for next! Fruit of an excellent collaboration between @telecomparis.bsky.social & @valeoai.bsky.social

I'm totally biased on this but I think it's wonderful that we now have official NeurIPS parallel satellite events. Parallelization was the trick that allowed us to scale to large data and models. It makes sense to try it for conferences as the community grows.

🚨 Happening NOW! 🎓 Our PhD student Victor Letzelter @vletzelter.bsky.social is currently defending his thesis at Telecom Paris! Good luck, Victor! 👏🚀 #PhDDefense #TelecomParis

3DV starts TODAY! The valeo.ai team is thrilled to be there to present our latest research focusing on advancing LiDAR segmentation #3DV #3DV2026 #3D #LiDAR Check out the below for details! 👇

Congratulations to our researchers Renaud Marlet and @abursuc.bsky.social on their repeated recognition as outstanding reviewers at #CVPR, #ICCV, and #ECCV👏👏👏 Thank you for your sharp insights, kindness, and dedication. It's key for the field to count on reviewers like you!

ELLIOT partners came together in Modena. 🤝 With 34 partners across 13 countries, the consortium met this week to review progress, discuss challenges and align on next steps, strengthening collaboration across Europe. 🌍

CLIP's visual embedding projector is a few-shot cornucopia 💡Few-shot adaptation of VLMs by fine-tuning the last matrix of the vision encoder 📜https://arxiv.org/abs/2410.05270 💻code available ✅ by M. Fahes, @tuanhungvu.bsky.social, @abursuc.bsky.social, @ptrkprz.bsky.social, R. de Charette

Tune in to the live PhD defense of Loïck Chambon on "Efficient Representations for Autonomous Driving", a PhD co-advised by @mlia-isir.bsky.social & @valeoai.bsky.social www.youtube.com/live/uFMAHn0...

Energized and inspired after our annual meetup to brainstorm on new exciting ideas and plan the projects ahead of us this year! As always this is an excellent occasion to fit (almost) the entire team in a single photo

IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adap... Yuan Yin, Shashanka Venkataramanan, Tuan-Hung Vu, Andrei Bursuc, Matthieu Cord Action editor: Ofir Lindenbaum https://openreview.net/forum?id=aLmQeZx2pR #projector #adaptation

The unreasonable magic of simplicity! Meet DrivoR (Driving on Registers): our latest end2end autonomous driving model. We teared down complex dependencies & modules from current models to obtain a pure Transformer-based SOTA driving agent (NAVSIM v1 & v2, HUGSIM). Find out more 👇

1/🧵 Q: Can we have both a simple and SOTA architecture in autonomous driving? R: Yes! 😍 Introducing Driving on Registers (DrivoR): a pure Transformer backbone that achieves SOTA results in NAVSIM v1 / v2 and closed-loop HUGSIM evaluation. Here is how 👇

Our @spyrosgidaris.bsky.social is speaking this morning (Wed, Dec 10th, 11:00 am Paris time) about "Latent Representations for Better Generative Image Modeling" in the Hi! PARIS - ELLIS monthly seminar. The talk will be live-streamed: www.hi-paris.fr/2025/09/26/a...

Perfect timing for this keynote on open, re-purposable foundation models at #aiPULSE2025 @abursuc.bsky.social taking the stage this afternoon! 👇

Check out our works at @NeurIPSConf #NeurIPS2025 this week! We present 5 full papers + 1 workshop about: 💡 self-supervised & representation learning 🖼️ generative image models 🧠 finetuning and understanding LLMs & multimodal LLMs 🔎 feature upsampling valeoai.github.io/posts/neurip...

We fermented our thoughts on understanding LoRA & ended up with IPA🍺 We found an asymmetry in LoRA: during training, A changes little & B eats most task-specific adaptation. So we pre-train A to preserve information before adaptation w/ excellent parameter efficiency #NeurIPS2025 #CCFM 👇

1/Serve your PEFT with a fresh IPA!🍺 Finetuning large models is cheaper thanks to LoRA, but is its random init optimal?🤔 Meet IPA: a feature-aware alternative to random projections #NeurIPS2025 WS #CCFM Oral+Best Paper Work w/ S. Venkataramanan @tuanhungvu.bsky.social @abursuc.bsky.social M. Cord 🧵

That was a cool project brillantly led by Ellington Kirby during his internship. We were curious if we could train diffusion models on sets of point coordinates. For images, this is a step towards spatial diffusion, with pixels reorganizing themselves, instead of diffusing in rgb values space only.

Check out NAF: an effective ViT feature upsampler to produce excellent (and eye-candy) pixel-level feature maps. NAF outperform both VFM-specific upsamplers (FeatUp, JAFAR) and VFM-agnostic methods (JBU, AnyUp) over multiple downstream tasks 👇

Need pixel-level features from your backbone (DINOv3, CLIP, RADIO, FRANCA...)? 🚀Introducing NAF: A universal, zero-shot feature upsampler. It turns low-res ViT features into pixel-perfect maps. -⚡ Model-agnostic -🥇 SoTA results -🚀 4× faster than SoTA -📈 Scales up to 2K res

The team is at BMVC'25 @bmvcconf.bsky.social to present three papers tackling challenges in 3D vision! We are presenting new works on: ✨ Diffusion for LiDAR point-clouds 🌙 Depth estimation with light enhancement 🔄 Multimodal distillation for 3D semantic segmentation 👇 #BMVC2025

Honored to host a very special guest today: Huy V. Vo, PhD alumnus of @valeoai.bsky.social He presented his work on automatic data-curation strategies for self-supervised representation learning (DINOv2, DINOv3). Find out more about his research here: huyvvo.github.io

Thrilled to have Jayneel Parekh visiting us over a break in the CVPR sprint to talk about his exciting works in analyzing MLLMs representations. Check out his great work jayneelparekh.github.io

Privileged to the diffusion master @nicolasdufour.bsky.social give to our team (full house) a tour of his excellent works in data and compute efficient diffusion models and a sneak preview of his latest MIRO work. Check it out 👌

Our recent research will be presented at @iccv.bsky.social! #ICCV2025 We’ll present 5 papers about: 💡 self-supervised & representation learning 🌍 3D occupancy & multi-sensor perception 🧩 open-vocabulary segmentation 🧠 multimodal LLMs & explainability valeoai.github.io/posts/iccv-2...

The PhD graduation season in the team goes on! Today, Corentin Sautier is defending his PhD on "Learning Actionable LiDAR Representations without Annotations". Good luck! 🚀

“Has anyone heard about DUSt3R?” All hands and hearts up in the room. Honored to welcome @gabrielacsurka.bsky.social today to speak about the amazing work @naverlabseurope.bsky.social towards 3D Foundation Models

It’s PhD graduation season in the team! Today, @bjoernmichele.bsky.social is defending his PhD on "Domain Adaptation for 3D Data" Best of luck! 🚀

Congratulations to our lab colleagues who have been named Outstanding Reviewers at #ICCV2025 👏 Andrei Bursuc @abursuc.bsky.social Anh-Quan Cao @anhquancao.bsky.social Renaud Marlet Eloi Zablocki @eloizablocki.bsky.social @iccv.bsky.social iccv.thecvf.com/Conferences/...

CoRL 2025 is just around the corner in Seoul, Korea! 🤖 🚗 We're excited to present our latest research and connect with the community. #CoRL2025

We're thrilled to join the ambitious ELLIOT project towards European large open-multimodal foundation models. The project kick-off is today!

ELSA will be extended!🎉 The European Commission decided to extend the duration of our Lighthouse on Secure and Safe AI. We will now run for an additional 12 months until August 2026. Find more details in the official press release: elsa-ai.eu/official-ext... Congratulations to the network!

Check out our MOCA self-supervised learning approach unifying the learning principles of both discriminative & masked image modelling paradigms. With a non-linear path, MOCA has been accepted at #TMLR and presented in the TMLR poster session at #iclr2025

Check out DIP (Dense In-context Post-training) @iccv.bsky.social: an effective post-training strategy to unleash dense awareness of features from your favorite pre-trained encoder (DINOv2, CLIP, MAE) We leverage meta-learning-like pseudo-tasks w/ pseudo-labels. Kudos @ssirko.bsky.social 👇 #iccv2025

How to make your DINOv2 excel at dense in-context scene understanding tasks. Check out DIP an effective post-training strategy by @ssirko.bsky.social @spyrosgidaris.bsky.social ‬ @vobeckya.bsky.social ‬@abursuc.bsky.social and Nicolas Thome 👇 #iccv2025

Hey #IV2025, @t-martyniuk.bsky.social is presenting her LiDPM work today! tl;dr: LiDPM - a point diffusion strategy for scene completion from outdoor LiDAR point clouds. Check out the paper and code below if you can't make it for the poster.

🚀Thrilled to introduce JAFAR—a lightweight, flexible, plug-and-play module that upsamples features from any Foundation Vision Encoder to any desired output resolution (1/n) Paper : arxiv.org/abs/2506.11136 Project Page: jafar-upsampler.github.io Github: github.com/PaulCouairon...

Just back from CVPR@Paris 🥐, what a fantastic event! Great talks, great posters, and great to connect with the French & European vision community. Kudos to the organizers, hoping that it returns next year! 🤞 #CVPR2025 @cvprconference.bsky.social

Great to see our team presenting their work at #ICLR2025! Here are a few moments captured from the conference. 📸

👏 Huge congrats to our research scientist Elias Ramzi for winning the AFRIF 2024 PhD award for his thesis "Robust image retrieval with deep learning", conducted at CNAM. Well deserved recognition for amazing work! 🏆 🔗 afrif.irisa.fr?page_id=54

Our recent research will be presented at #ICLR2025 @iclr_conf: VLMs, LLMs, diffusion models, self-supervised learning, physics-informed learning… Find out more below 🧵 valeoai.github.io/posts/2025-0...

We have a very special guest visiting us today: the one and only Alyosha Efros

🚗 Ever wondered if an AI model could learn to drive just by watching YouTube? 🎥👀 We trained a 1.2B parameter model on 1,800+ hours of raw driving videos. No labels. No maps. Just pure observation. And it works! 🤯 🧵👇 [1/10]

We've just had our annual gathering to get together and brainstorm on new exciting ideas and projects ahead -- stay tuned! This is also an excellent occasion to fit all team members in a photo 📸

📚🔍Excited to share our work at #NeurIPS2024! Dive into representation learning, optimization, explainability, VLMs & LLMs, and more. Check out our blog post to know more about our 7 papers: valeoai.github.io/posts/2024-1... 🧵👇