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/...

Update: ResearchGate has investigated the case, and, as far as I can see, all the suspicious papers (~200) have now been removed. Many thanks to the @researchgate.bsky.social team!

Three papers accepted to #NeurIPS2025 (one spotlight)! 🎉 Awesome works in generative modeling, multi-token prediction, and future prediction. Congratulations to all collaborators! @nasosger.bsky.social, sta8is.bsky.social, @nicolabourbaki.bsky.social, @ikakogeorgiou.bsky.social & N. Komodakis!

Discovered that our RangeViT paper keeps being cited in what might be LLM-generated papers. Number of citations increased rapidly in the last weeks. Too good to be true. Papers popped up on different platforms, but mainly on ResearchGate with ~80 papers in just 3 weeks. [1/]

1/ Can open-data models beat DINOv2? Today we release Franca, a fully open-sourced vision foundation model. Franca with ViT-G backbone matches (and often beats) proprietary models like SigLIPv2, CLIP, DINOv2 on various benchmarks setting a new standard for open-source research.

1/ New & old work on self-supervised representation learning (SSL) with ViTs: MOCA ☕ - Predicting Masked Online Codebook Assignments w/ @spyrosgidaris.bsky.social O. Simeoni, A. Vobecky, @matthieucord.bsky.social, N. Komodakis, @ptrkprz.bsky.social #TMLR #ICLR2025 Grab a ☕ & brace for a story & a🧵

1/n 🚀New paper out - accepted at #ICCV2025! Introducing DIP: unsupervised post-training that enhances dense features in pretrained ViTs for dense in-context scene understanding Below: Low-shot in-context semantic segmentation examples. DIP features outperform DINOv2!

🚀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...

Are you at @cvprconference.bsky.social? Come by our poster! 📅 Sat 14/6, 10:30-12:30 📍 Poster #395, ExHall D

I am at #CVPR2025 this week in Nashville! Presenting "Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers" on multi-modal semantic future prediction. Come discuss! Fri 13 Jun 10:30-12:30, poster #345 bsky.app/profile/sta8...

1/n Introducing ReDi (Representation Diffusion): a new generative approach that leverages a diffusion model to jointly capture – Low-level image details (via VAE latents) – High-level semantic features (via DINOv2)🧵

The @valeoai.bsky.social team is presenting a few exciting works @iclr-conf.bsky.social this year on masked generative transformers, adaptation of VLMs, self-supervised representation learning, neural solvers. #iclr2025 Check them out 👇

Nice research work from @nicolabourbaki.bsky.social et al. Enhances latent generative models by regularizing the VAE's latent space with an equivariance loss. The finetuning process is straightforward + demonstrates improvements in just 5 epochs! 📄 arxiv.org/abs/2502.09509 🐍 github.com/zelaki/eqvae

Still mesmerized by this work and its results: a mid-to-end driving agent trained with self-play on just 8 maps on 1.6B km of driving (9500 years of subjective driving experience) smashes in off-the-shelf manner all existing benchmarks (nuPlan, CARLA, Waymax) 😮

EQ-VAE: Such a simple & cool trick to regularize multiple kinds of autoencoders: align reconstruction of transformed latents w/ the corresponding transformed inputs. 🚀REPA: 4x training speedup 🚀MaskGIT: 2x training speedup 🚀DiT-XL/2: 7x faster convergence Kudos @nicolabourbaki.bsky.social et al.

The things I've found hardest about research have all been non-technical: maintaining confidence and self-esteem, not abandoning the work when it's too hard or stressful, finding time to learn new things. In comparison, the technical parts are much easier

🚨 Just a quick note that following requests, we trained a 512px version of our Coherence-Aware Diffusion model (CVPR'24) and updated the paper on arxiv: arxiv.org/abs/2405.20324 It has a package and pretrained models! 🖥️ nicolas-dufour.github.io/cad.html 🤖 github.com/nicolas-dufo...

1/n🚀If you’re working on generative image modeling, check out our latest work! We introduce EQ-VAE, a simple yet powerful regularization approach that makes latent representations equivariant to spatial transformations, leading to smoother latents and better generative models.👇

1/n 🚀 Excited to share our latest work: DINO-Foresight, a new framework for predicting the future states of scenes using Vision Foundation Model features! Links to the arXiv and Github 👇

This amazing team ❤️

Thrilled to announce our workshop on Embodied Intelligence for Autonomous Systems on the Horizon @cvprconference.bsky.social featuring a crazy line-up of speakers and challenges. Mark it in your agendas and also in your registration #cvpr2025 opendrivelab.com/cvpr2025/wor...