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

Language technology to seamlessly communicate in an increasingly connected world: understanding, generation, translation, speech, modelling.

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.

Data, code and models released by NAVER LABS Europe.

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

LeBenchmark: a reproducible framework for assessing self-supervised representation learning from speech

Solene Evain, Ha Nguyen, Hang Le, Marcely Zanon Boito, Salima Mdhaffar, Sina Alisamir, Ziyi Tong, Natalia Tomashenko, Marco Dinarelli, Titouan Parcollet, Alexandre Allauzen, Yannick Esteve, Benjamin Lecouteux, Francois Portet, Solange Rossato, Fabien Ringeval, Didier Schwab, Laurent Besacier

Interspeech, Brno, Czech Republic, 30 August-3 September 2021

Impact of encoding and segmentation strategies on end-to-end simultaneous speech translation

Ha Nguyen, Yannick Estève, Laurent Besacier

Interspeech, Brno, Czech Republic, 30 August - 3 September 2021

Do multilingual neural machine translation models contain language pair specific attention heads?

Zae Myung Kim, Laurent Besacier, Vassilina Nikoulina, Didier Schwab

Findings of the Annual Meeting of the Association for Computation Linguistics (ACL) 2021, virtual event, 1-6 August, 2021

Demonstration-conditioned reinforcement learning for few-shot imitation

Theo Cachet, Julien Perez, Christopher Dance

Proceedings of the 38th International Conference on Machine Learning (ICML), PMLR 139:2376-2387, 2021
DCRL A new family of approaches to few-shot imitation

A new family of approaches to few-shot imitation

A new approach to learning few-shot imitation agents whereby you simply feed demonstrations of a new test task to the learned policy called DCRL. This new approach has several advantages.

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SPLADE – a sparse bi-encoder BERT-based model achieves effective and efficient first-stage ranking

A new sparse bi-encoder BERT-based model for effective and efficient first-stage ranking. The first to rival dense models.  

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Continual learning of visual representations without catastrophic forgetting

Using domain randomization and meta-learning, computer vision models forget less when exposed to training samples from new domains. Remembering is a crucial element in the deployment of self-driving cars and robots which interact in dynamic environments.

INTERSPEECH 2021

INTERSPEECH 2021, hybrid event, Brno, Czech Republic

30th August - 3rd September 2021, hybrid event, physically in Brno, Czech Republic, and also virtually.
3 accepted papers
   
acl-ijcnlp2021

ACL-IJCNLP 2021

1-6 August (virtual). Presenting 2 papers on NMT and a workshop paper on EBMs for programming. Silver sponsor. We're hiring!
   
ICML2021

International Conference on Machine Learning (ICML) 2021

18th-24th July 2021
Demonstration-conditioned reinforcement learning for few-shot imitation

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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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