Interested in unsupervised domain adaptation for LiDAR data ? Then, I am happy to see you at the spotlight presentation of our paper “SALUDA” this afternoon at 15:00 or at the poster session International Conference on 3D Vision. Paper: arxiv.org/abs/2304.03251 Code: github.com/valeoai/SALUDA

.Victor Letzelter will be at #ICML2024 to present his work on leveraging the geometric properties of the Winner-takes-all learners for conditional density estimation & uncertainty prediction, w/o modifying its original training scheme. Find a tl;dr below & come say hi at the posters

Glad to announce that Stem-JEPA has been accepted to ISMIR Conference ! In this work, we tackle the task of musical stem compatibility estimation (what “fits” together) as a representation learning problem. (1/7) Paper: arxiv.org/abs/2408.02514 Code: github.com/SonyCSLParis/S…

You have an already trained sem. segmentation model ? You want to apply it to data with a domain shift ? You are afraid of degradation during the adaptation ? Then you might want to check out our work TTYD at European Conference on Computer Vision #ECCV2026 2024 in Milan. 👉 Poster # 73: Tuesday, 16:30 #ECCV2024

🌟 Calling all MSc students passionate about computer vision and ML! We’re offering research internships about diffusion models, multi-modal transformers, continual learning, & more. 4 exciting openings await! 🔗 Learn more: valeoai.github.io/interns/ RT to spread the word! 🙌

Inferring 3D human poses from video is highly ill-posed because of depth ambiguity. Our work accepted to #NeurIPS2024, ManiPose, gets one step closer to solving this, by leveraging prior knowledge about poses topology and cool multiple-choice learning techniques.

🚗 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]

Let’s catch up if you’re at ICML Conference and want to chat!