Our technical expertise is enriched with a deep understanding of how people interact with technology.
No tracking until you click to share
Computer vision
Research in a wide range of areas, including visual search, scene parsing, human sensing, action recognition, 3D reconstruction, and embedded deep vision.
3D Vision
In an ambient intelligence world, which involves robots and self-driving vehicles, we naturally need to have a good understanding of the 3D world we live in.
Search and Recommendation
Human-centric search and recommendation interfaces are key to enabling a world of ambient intelligence.
Machine Learning and Optimization
Innovative models to design algorithms and imagine new tasks that push the boundaries and bring to life intelligent systems in our everyday lives.
Natural Language Processing
Language is the most natural and dominant mode of communication. We create technology to seamlessly communicate with devices in an ambient intelligent world.
UX and Ethnography
Getting a deep understanding of our environment to design services with which we can seamlessly interact.
Systemic AI
At the crossroads of AI and software engineering research, addressing the challenges of integrating AI/ML components.
Some of the big cross-disciplinary challenges we address:
Representation learning: turning all data entities (text, images, videos, web pages, emails, …) into semantically-rich representations to that can be efficiently processed, mined and related to each other.
Interactive learning: including the human in the learning loop to benefit from the complementary capabilities of humans and machines
Lifelong learning: exploring how to learn and manage prediction systems, policies or processes in a sustainable manner, i.e. in a manner that makes maximum reuse of previous experiences.
Machine reasoning: connecting existing pieces of knowledge to create new knowledge, e.g. being able to answer complex questions that require multiple supporting facts.
Decision making: learning how to make actionable decisions in uncertainty, especially in ever-changing environments
Agility: we live in an ever-changing world which means the technology we use must evolve in synergy with the people and business processes that touch it.
User centric: an important challenge in any technology is to the adoption by people. Only then does science become innovation. Our solutions are grounded in a deep understanding of how people work and how technology can help them every day.
The AI for Robotics theme comprises work from multiple research groups.
Collaboration
NAVER Labs Europe is a hub of NAVER’s global AI R&D Belt, a network of centres of excellence in Korea, Japan, Vietnam & Europe. By collaborating with different partners we aim to make AI technology in South East Asia and Europe more competitive.
Our scientists collaborate with national and international partners, academics and businesses to solve problems and invent technology and services that will have impact in the real world.
We're releasing a state-of-the-art multilingual and multi-domain neural machine translation model specialised for biomedical data that enables translation into English from five languages (French, German, Italian, Spanish and Korean).
A new platform based on deep-learning approaches to handwritten-text recognition and information extraction enables data from century-old documents to be parsed and analysed, making it possible to explore epidemics and the evolution of populations over time.
We use cookies to ensure that you have the best experience on our site. If you continue to use the latter, we will consider that you accept the use of cookies. Disable cookies : Chrome - Firefox - Safari - Opera - Naver WhaleAcceptPrivacy policy
