Research - NAVER LABS Europe

RESEARCH

We create new connections through advanced research and technology in vision, text, machine learning, UX and ethnography.
Our multidisciplinary approach to AI allows us to tackle challenges from different perspectives and gives greater meaning to our work.

Computer Vision

Visual search, scene parsing, human sensing, action recognition, pose estimation and lifelong learning for AR, robotics, search and autonomous driving.

3D Vision

In a connected world of people, 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, multimodal strategies and modules built on accountable algorithms for transparency and trust.

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

As the most natural and dominant mode of communication, we create language technology to seamlessly communicate with devices in a connected 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.
Code and data

Data, code and models released by NAVER LABS Europe.

Seminars

Connect to our online seminars given by expert speakers from around the world

RECENT PUBLICATIONS

A white box analysis of ColBERT

Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant

European Conference on Information Retrieval (ECIR), Lucca, Italy (online event), 28 March-3 April, 2021

Unsupervised meta-domain adaptation for fashion retrieval

Vivek Sharma, Naila Murray, Diane Larlus, M. Saquib Sarfraz, Rainer Stiefelhagen, Gabriela Csurka

Winter Conference on Applications of Computer Vision (WACV), virtual event, 5-9 January, 2021

StacMR: Scene-text aware cross-modal retrieval

Andres Mafla, Rafael Sampaio De Rezende, Lluis Gomez, Diane Larlus, Dimosthenis Karatzas

Winter Conference on Applications of Computer Vision (WACV), virtual event, 5-9 January, 2021

Vital records: uncover the past from historical handwritten records

Hervé Déjean, Jean-Luc Meunier

The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, held in conjunction with COLING 2020, Barcelona, Spain (virtual event), 12 December, 2020
BLOG
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A white box analysis of ColBERT

By dissecting the matching process of the recent ColBERT model, we make a step towards unveiling the ranking properties of BERT-based ranking models and show that ColBERT (implicitly) learns a notion of term importance that correlates with IDF.

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Running into the unknown with RunAhead

Running into the unknown with RunAhead: finding pleasant running tours and intuitively navigating through them. The use of combinatorial optimization and UX design, together with head-tracking technology, provides a non-intrusive way of helping runners to discover new itineraries.

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SuperLoss: Robust curriculum learning helps machines to learn like humans

A novel framework which uses individual sample losses as error measures to determine the relative difficulty of samples in a dataset. Can be plugged on top of existing neural network models to implement curriculum learning for any task, even with noisy datasets.

RECENT NEWS
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ALPS – Advanced Language Processing winter school in the French Alps

17th -  22nd January 2021, Autrans, France Co-organized by LIG (University Grenoble Alpes) and NAVER LABS Europe, ALPS
WACV 2021

Winter Conference on Applications of Computer Vision (WACV) 2021

5th - 9th January 2021
Virtual event. Two papers; one on fashion retrieval and another on cross-modal retrieval
sighum

LaTeCH-CLfL 2020: Joint SIGHUM workshop on computational linguistics for cultural heritage, social sciences, humanities and literature

12th December 2020
Paper: Vital records: uncover the past from historical handwritten records

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Collaboration

global ai belt

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.

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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.

Discover how our research is recognized.

About NAVER LABS Europe

NAVER LABS Europe is France’s biggest industrial research centre in artificial intelligence.

NAVER LABS is an R&D subsidiary of NAVER responsible for future technology.

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