🚗🌐 Working on domain adaptation for 3D point clouds / LiDAR? 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 PhD graduation season in the team goes on! Today, Corentin Sautier is defending his PhD on "Learning Actionable LiDAR Representations without Annotations". Good luck! 🚀

Tetiana Martyniuk@t-martyniuk.bsky.social · 11mo ago

Another great event for @valeoai.bsky.social team: a PhD defense of Corentin Sautier. 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).

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! 🚀

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!

Gilles Puy@gillespuy.bsky.social · 11mo ago

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/]

If you're interested in human pose estimation and mesh recovery from LiDAR data, we have this massive survey: arxiv.org/abs/2509.12197 Salma and Nermin put a tremendous amount of work in it, there's everything: the tasks, all the methods organized, datasets, numbers, challenges and opportunities.

3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review

In this paper, we present a comprehensive review of 3D human pose estimation and human mesh recovery from in-the-wild LiDAR point clouds. We compare existing approaches across several key dimensions, ...

arxiv.org

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.

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

Tetiana Martyniuk@t-martyniuk.bsky.social · last yr.

Our paper "LiDPM: Rethinking Point Diffusion for Lidar Scene Completion" got accepted to IEEE IV 2025! 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/

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!

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 😉

🚨 New preprint! How far can we go with ImageNet for Text-to-Image generation? w. @arrijitghosh.bsky.social @lucasdegeorge.bsky.social @nicolasdufour.bsky.social @vickykalogeiton.bsky.social TL;DR: Train a text-to-image model using 1000 less data in 200 GPU hrs! 📜https://arxiv.org/abs/2502.21318 🧵👇

We @imagineenpc.bsky.social are slowly but surely entering our proposals for master's degree internships here: docs.google.com/document/d/1... These are 6 months projects that typically correspond to the end-of-study project in the French curriculum. Probably more offers to come, check it regularly.

2025 IMAGINE Internships

2025 Internship proposals at IMAGINE IMAGINE is a top research group on computer vision and machine learning. It is part of the LIGM lab and hosted at École des Ponts ParisTech (ENPC), about 25 min f...

docs.google.com