Alexandre Boulch
@alexandreboulch.bsky.social
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Senior researcher valeo.ai. Member of INRIA-Valeo ASTRA team. Website: boulch.eu
reposted by
Alexandre Boulch
Björn Michele
6 months ago
For more details 📝 Paper:
bmva-archive.org.uk/bmvc/2025/a...
💻 Code:
github.com/valeoai/muddos
This is a joint work with my great co-authors
@alexandreboulch.bsky.social
,
@gillespuy.bsky.social
,
@tuanhungvu.bsky.social
, Renaud Marlet,
@ncourty.bsky.social
and myself.
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GitHub - valeoai/muddos: Official repository of the BMVC 2025 paper "Improving Multimodal Distillation for 3D Semantic Segmentation under Domain Shift"
Official repository of the BMVC 2025 paper "Improving Multimodal Distillation for 3D Semantic Segmentation under Domain Shift" - valeoai/muddos
https://github.com/valeoai/muddos
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reposted by
Alexandre Boulch
valeo.ai
6 months ago
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
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reposted by
Alexandre Boulch
Nicolas Audebert
11 months ago
Pour les collègues francophones, vous saviez que le FID était tout cassé ? Moi non plus. Pourtant, si on s'y prend bien, on peut calculer le FID avec moins de 1000 images. J'en parlerai au GRETSI fin août :
hal.science/hal-05142942
👀
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Évaluation des générateurs d'images à partir de peu d'exemples : calculer le FID avec 10 fois moins d'images, c'est possible
La distance Inception de Fréchet (Fréchet Inception Distance ou FID) est une métrique standard pour l'évaluation des modèles génératifs images. Construite sur la distance de Wasserstein, le FID mesure...
https://hal.science/hal-05142942
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reposted by
Alexandre Boulch
valeo.ai
11 months ago
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
add a skeleton here at some point
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reposted by
Alexandre Boulch
Tetiana Martyniuk
11 months ago
We just released the code of
#LiDPM
, go ahead and play with it (and don't forget to star 🤭🤩)! Training and inference code available, along with the model checkpoint. Github repo:
github.com/astra-vision...
#IV2025
add a skeleton here at some point
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reposted by
Alexandre Boulch
Tetiana Martyniuk
11 months ago
Presenting our project
#LiDPM
in the afternoon oral session at
#IV2025
! Project page:
astra-vision.github.io/LiDPM/
w/
@gillespuy.bsky.social
,
@alexandreboulch.bsky.social
, Renaud Marlet, Raoul de Charette Also, see our poster at 3pm in the Caravaggio room and AMA 😉
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reposted by
Alexandre Boulch
Tetiana Martyniuk
11 months ago
Okay that was stressful 🥲
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reposted by
Alexandre Boulch
Paul Couairon
11 months ago
🚀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...
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reposted by
Alexandre Boulch
valeo.ai
over 1 year ago
🚗 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]
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reposted by
Alexandre Boulch
Andrei Bursuc
over 1 year ago
This amazing team ❤️
add a skeleton here at some point
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reposted by
Alexandre Boulch
Loïc Landrieu
over 1 year ago
Check out our new work with
@gastruc.bsky.social
and
@nicaogr.bsky.social
and Clément Mallet! The one-stop shop for multimodal Earth Observation 🤩
add a skeleton here at some point
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reposted by
Alexandre Boulch
Loïc Landrieu
over 1 year ago
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🧵👇
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reposted by
Alexandre Boulch
F. Güney
over 1 year ago
I could easily spend an afternoon looking at the results of this paper:
motionmodes.github.io
or this paper:
rollingdepth.github.io
or this paper:
romosfm.github.io
vision is cool 😎
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Motion Modes: What Could Happen Next?
Motion Modes is the first training-free method to generate multiple plausible yet distinct motions for a given object, disentangled from the motion of other objects, camera and other scene changes, fr...
https://motionmodes.github.io/
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At INRIA Paris for
@anhquancao.bsky.social
for his PhD defense. Subject is Learning Semantics and Geometry for Scene Understanding.
anhquancao.github.io
over 1 year ago
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