Bio

I am a Staff Research Scientist at DeepMind. I obtained a Ph.D. from the Sierra and Willow groups. I was supervised by Simon Lacoste-Julien, Ivan Laptev and Josef Sivic. Before that, I graduated from Ecole polytechnique and Telecom ParisTech in 2015 and got a Masters Degree in Mathematics, Machine Learning and Computer Vision (MVA). My work focuses on structured learning from video and natural language. More details can be found in my resume.

Invited talks

Leave Those Nets Alone: Advances in Self-Supervised Learning
Tutorials, CVPR 2021.
Towards Versatile and Powerful Multimodal networks
The 6th International Challenge on Activity Recognition, CVPR 2021.
Representation Learning from Unlabeled Narrated Videos
Computer Vision and Deep Learning Summit, Machine Can See 2020.
Learning from Narrated Videos
The 3rd Workshop on YouTube-8M Large-Scale Video Understanding, ICCV 2019.

Selected publications

ūü¶©Flamingo: a Visual Language Model for Few-Shot Learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andrew Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan
In arXiv, 2022.
Perceiver IO: A general architecture for structured inputs & outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier H√©naff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, and JońĀo Carreira.
In Proc. ICLR 2022.
Thinking Fast and Slow: Efficient text-to-visual retrieval with transformers
Antoine Miech, Jean-Baptiste Alayrac, Ivan Laptev, Josef Sivic and Andrew Zisserman.
In Proc. CVPR 2021.
Self-Supervised MultiModal Versatile Networks
Jean-Baptiste Alayrac, Adri√† Recasens, Rosalia Schneider, Relja Arandjelovińá, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman.
In Proc. NeurIPS 2020.
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Antoine Miech, Jean-Baptiste Alayrac, Lucas Smaira, Ivan Laptev, Josef Sivic and Andrew Zisserman.
In Proc. CVPR 2020. (oral).
Visual Grounding in Video for Unsupervised Word Translation
Gunnar Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira, Mateusz Malinowski, Joao Carreira, Phil Blunsom and Andrew Zisserman.
In Proc. CVPR 2020.
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac, Makarand Tapaswi, Ivan Laptev, Josef Sivic.
In Proc. ICCV 2019.
Are Labels Required for Improving Adversarial Robustness?
Jonathan Uesato, Jean-Baptiste Alayrac, Po-Sen Huang, Robert Stanforth, Alhussein Fawzi, Pushmeet Kohli.
In Proc. NeurIPS 2019.
The Visual Centrifuge: Model-Free Layered Video Representations
Jean-Baptiste Alayrac, Joao Carreira, Andrew Zisserman.
In Proc. CVPR 2019. (oral).
Cross-task weakly supervised learning from instructional videos
Dimitri Zhukov, Jean-Baptiste Alayrac, Ramazan Gokberk Cinbis, David Fouhey, Ivan Laptev, Josef Sivic.
In Proc. CVPR 2019.
SeaRnn: Training RNNs with Global-Local Losses
Rémi Leblond, Jean-Baptiste Alayrac, Anton Osokin and Simon Lacoste-Julien.
Accepted to ICLR 2018.
Joint Discovery of Object States and Manipulation Actions
Jean-Baptiste Alayrac, Josef Sivic, Ivan Laptev and Simon Lacoste-Julien.
In Proc. ICCV 2017.
Learning from Video and Text via Large-Scale Discriminative Clustering
Antoine Miech, Jean-Baptiste Alayrac, Piotr Bojanowski, Ivan Laptev and Josef Sivic.
In Proc. ICCV 2017 (Spotlight).
Unsupervised learning from narrated instruction videos
Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Ivan Laptev, Josef Sivic and Simon Lacoste-Julien.
In Proc. CVPR 2016 (Oral).

PhD Thesis

Structured Learning from Videos and Language
Jean-Baptiste Alayrac

Teaching

Statistical machine learning - Master M1 - Ecole normale supérieure, TA, 2015-2016.
1M001 : Analyse et algèbre pour les sciences, Universite Pierre et Marie Curie, TA, 2014-2016.
1M004 : Calcul matriciel, Universite Pierre et Marie Curie, TA, 2014-2016.
2M223 : Algèbre bilinéaire et géométrie, Universite Pierre et Marie Curie, TA, 2014-2015.

Other projects

Simple sketch recognizer used in an exhibition at Palais de la Découverte.