AI for robotics - interaction with humans - NAVER LABS Europe
AI For Robotics Human Robot Interaction

To help and support us in our daily life, communication and interaction with robots must be efficient and stress-free. Human language and gestures are natural and rich sources of information that can be used to assign or even explain tasks to a robot who, in turn, should communicate their actions and intentions to those in their surroundings and specifically to the people they collaborate with. We investigate both areas i.e. new methods of human body pose and language understanding and interaction between humans and robots to ultimately integrate robots in our homes and workplaces in a way which is unobtrusive.

Publications

Blogs

PoseBERT
A novel, plug and play model for human 3D shape estimation of the body or hands, in videos which is trained by mimicking the BERT algorithm from the natural language processing community. Blog post by Fabien Baradel, Philippe Weinzaepfel, Romain Brégier, Yannis Kalantidis and Gregory Rogez
Risk Sensitive Robot Navigation
We explore how effectively a single policy learned by reinforcement learning can modulate robot behaviour, from risk-averse (cautious) to risk-neutral (maximizing the average reward). Blog by Chris Dance et al.
Moulding Humans blog article
Non-parametric 3D Human Shape Estimation from Single Images. Blog article by Gregory Rogez
Fine-grained action retrieval
Fine-grained action retrieval made possible thanks to a new annotated dataset and part-of-speech embedding. Blog article by Diane Larlus and Gabriela Csurka Khedari
Mimetics Blog
Recent work on human action recognition, specifically on understanding actions out of context thanks to our new Mimetics dataset. Blog article by Philippe Weinzaepfel and Gregory Rogez
One Method One Pipeline Blog Image
Using the KAPTURE pipeline and robust R2D2 method, we ranked 1st, 2nd and 4th in the VisLocOdomMap workshop challenge. Blog article by Martin Humenberger
Dope featured image
A novel efficient model for whole-body 3D pose estimation (including bodies, hands and faces), that is trained by mimicking the output of hand-, body- and face-pose experts. Blog article by Philippe Weinzaepfel

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