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Andrei Bursuc @CVPR
@abursuc
Research scientist @valeoai | Teaching @Polytechnique @ENS_ULM | Alumni @upb1818 @Mines_Paris @Inria @ENS_ULM | Feedback: admonymous.co/abursuc
Paris, France
Joined November 2008
Posts
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    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 👇
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    A visual exploration of Gaussian Processes: beautiful interactive plots and a brief tutorial to make GPs more approachable jgoertler.com/visual-explora…
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    DINO and DINOv2 are surely amazing SSL approaches. Many assume that they're also very simple (in particular vs. other SSL methods), but they are actually a bit more elaborate and I've been in awe of the achievement of the authors. This diagram from SimDINO is more complete.
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    Self-supervised learning is fantastic for pretraining, but can we use it for other tasks (kNN classification, in-context learning) & modalities, w/o training & by simply using its gradients as features? Enter 🍄FUNGI - Features from UNsupervised GradIents #NeurIPS2024 🧵
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    Decoder Denoising Pretraining for Semantic Segmentation: A fun and simple idea for pre-training the decoder for semantic segmentation arxiv.org/abs/2205.11423 1/
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    An excellent poor man's visual prompt engineering strategy for CLIP: draw red circles on an object in an image auto-magically focuses its attention on that region, leading to a specific embedding #ICCV2023
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    Our work on learning to perform semantic segmentation without human supervision by driving around cities made it to #eccv2022 More info coming soon.
    Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation abs: arxiv.org/abs/2203.11160 project page: vobecant.github.io/DriveAndSegmen… @Gradio Demo: huggingface.co/spaces/vobecan…
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    ICCV: International CVPR Corrected Versions #cvpr2021 #iccv2021
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    When life gives you lemons, Andrea makes lemonade 🍋 Kudos to Andrea Vedaldi doing an excellent work presenting his paper in spite of an incident w/ the poster #cvpr2025
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    An intriguing #iclr2020 paper on self-supervision studied over a single image: iclr.cc/virtual_2020/p… Starting from an image the authors generate a 1M images dataset of crops and augmentations from this image 1/
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    Slides for most talks at Good Citizen at CVPR workshop are up cc.gatech.edu/~parikh/citize… Lots of useful advice and experience for writing and reviewing papers, how to do good research and evaluation, talks, how to organise your time #CVPR2018
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    The brilliant Little Book of Deep Learning by @francoisfleuret is here! 🤩 Hoping now for an autograph session at a CV/ML venue soon.
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    Leave Those Nets Alone: Advances in Self-Supervised Learning. Join us this Sunday for our #cvpr2021 tutorial to discover what's cooking these days in the different flavors of self-supervised learning. Recordings and slides will be online right after. gidariss.github.io/self-supervise…
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    On the CLIP vs. SSL image encoder debate: an overlooked aspect is how much fewer GPU resources SSL models need compared to CLIP ones for pretraining. Recent examples: - SSL: Franca - 128 H100, bsz 3K; DINOv3 - 256 H100, bsz 4K - CLIP: SigLIP2 - 2048 TPUv5, bsz 32K; PE - bsz 131K