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!
🚀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
🚀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
We'll present MuDDoS at BMVC: a method that boosts multimodal distillation for 3D semantic segmentation under domain shift.
📍 BMVC
🕚 Monday, Poster Session 1: Multimodal Learning (11:00–12:30)
📌 Hadfield Hall #859
We'll present MuDDoS at BMVC: a method that boosts multimodal distillation for 3D semantic segmentation under domain shift.
📍 BMVC
🕚 Monday, Poster Session 1: Multimodal Learning (11:00–12:30)
📌 Hadfield Hall #859
The team is proud to announce that several paper were accepted at #NeurIPS25. Looking forward to meet in Paris (25th-26th Nov), Copenhagen or San Diego (1st-7th Dec)!
Let's present our papers ⬇️
The team is proud to announce that several paper were accepted at #NeurIPS25. Looking forward to meet in Paris (25th-26th Nov), Copenhagen or San Diego (1st-7th Dec)!
Let's present our papers ⬇️
His thesis focused on structured visual representations:
• VidEdit - zero-shot text-to-video editing
• DiffCut - zero-shot segmentation via diffusion features
• JAFAR - high-res visual representation upsampling
His thesis focused on structured visual representations:
• VidEdit - zero-shot text-to-video editing
• DiffCut - zero-shot segmentation via diffusion features
• JAFAR - high-res visual representation upsampling
First conference as a PhD student, really excited to meet new people.
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!
First conference as a PhD student, really excited to meet new people.
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...
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...
His thesis «Learning Actionable LiDAR Representations w/o Annotations» covers the papers BEVContrast (learning self-sup LiDAR features), SLidR, ScaLR (distillation), UNIT and Alpine (solving tasks w/o labels).
His thesis «Learning Actionable LiDAR Representations w/o Annotations» covers the papers BEVContrast (learning self-sup LiDAR features), SLidR, ScaLR (distillation), UNIT and Alpine (solving tasks w/o labels).
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!
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!
Paper : arxiv.org/abs/2506.11136
Project Page: jafar-upsampler.github.io
Github: github.com/PaulCouairon...
Paper : arxiv.org/abs/2506.11136
Project Page: jafar-upsampler.github.io
Github: github.com/PaulCouairon...
tldr: LiDPM enables high-quality LiDAR completion by applying a vanilla DDPM with tailored initialization, avoiding local diffusion approximations.
Project page: astra-vision.github.io/LiDPM/
tldr: LiDPM enables high-quality LiDAR completion by applying a vanilla DDPM with tailored initialization, avoiding local diffusion approximations.
Project page: astra-vision.github.io/LiDPM/
Registration is open (it's free) with priority given to authors of accepted papers: cvprinparis.github.io/CVPR2025InPa...
Big 🧵👇 with details!
Registration is open (it's free) with priority given to authors of accepted papers: cvprinparis.github.io/CVPR2025InPa...
Big 🧵👇 with details!
This is also an excellent occasion to fit all team members in a photo 📸
Many more missing, please let me know how is already in bsky to add them!
go.bsky.app/BowzivT
Many more missing, please let me know how is already in bsky to add them!
go.bsky.app/BowzivT