Olivier J. Hénaff

Senior Staff Research Scientist

Google DeepMind, London, UK

My research aims to understand the principles underlying biological and artificial intelligence. Humans and animals produce amazingly complex behaviors, in the face of changing environments and often with little to no supervision. This has led me to study the structure of neural representations in perceptual and physiological experiments, asking how our visual system might enable such behaviors.

At DeepMind, I have been investigating self-supervised algorithms that extract structure from raw data, enabling data-efficient image recognition, behaviorally-relevant scene understanding, and unsupervised object discovery and temporal correspondence. More recently, I have been interested in how visual representations might structure our memory, enabling flexible perceptual inference and long-video understanding.

Prior to joining DeepMind, I completed my PhD at NYU's Center for Neural Science, advised by Eero Simoncelli. Before starting research, I studied math and physics at École Polytechnique and Lycée Sainte Geneviève.

Talks

Publications

Data curation via joint example selection further accelerates multimodal learning

Talfan Evans, Nikhil Parthasarathy, Hamza Merzic, Olivier J. Hénaff

Neural Information Processing Systems (NeurIPS), December 2024 (Spotlight)

Memory Consolidation Enables Long-Context Video Understanding

Ivana Balažević, Yuge Shi, Pinelopi Papalampidi, Rahma Chaabouni, Skanda Koppula, Olivier J. Hénaff

International Conference on Machine Learning (ICML), May 2024 (Spotlight)

Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding

Talfan Evans, Shreya Pathak, Hamza Merzic, Jonathan Schwarz, Ryutaro Tanno, Olivier J. Hénaff

European Conference on Computer Vision (ECCV), February 2024

Towards In-context Scene Understanding

Ivana Balažević, David Steiner, Nikhil Parthasarathy, Relja Arandjelović, Olivier J. Hénaff

Neural Information Processing Systems (NeurIPS), December 2023 (Spotlight)

Self-supervised video pretraining yields human-aligned visual representations

Nikhil Parthasarathy, S. M. Ali Eslami, João Carreira, Olivier J. Hénaff

Neural Information Processing Systems (NeurIPS), December 2023

Object discovery and representation networks

Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelović

European Conference on Computer Vision (ECCV), October 2022

Primary visual cortex straightens natural video trajectories

Olivier J. Hénaff*, Yoon Bai*, Julie A. Charlton, Ian Nauhaus, Eero P. Simoncelli, Robbe L. T. Goris

Nature Communications, October 2021. *equal contribution

Efficient Visual Pretraining with Contrastive Detection

Olivier J. Hénaff, Skanda Koppula, Jean-Baptiste Alayrac, Aaron van den Oord, Oriol Vinyals, João Carreira

International Conference on Computer Vision (ICCV), October 2021 (Oral)

Divide and Contrast: Self-supervised Learning from Uncurated Data

Yonglong Tian, Olivier J. Hénaff, Aaron van den Oord

International Conference on Computer Vision (ICCV), October 2021

Data-Efficient Image Recognition with Contrastive Predictive Coding

Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aaron van den Oord

International Conference on Machine Learning (ICML), July 2020

Are we done with ImageNet?

Lucas Beyer*, Olivier J. Hénaff*, Alexander Kolesnikov*, Xiaohua Zhai*, Aäron van den Oord*

Tech report, June 2020. *equal contribution

Representation of visual uncertainty through neural gain variability

Olivier J. Hénaff, Zoe M. Boundy-Singer, Kristof Meding, Corey M. Ziemba, Robbe L. T. Goris

Nature Communications, May 2020

Perceptual straightening of natural videos

Olivier J. Hénaff, Robbe L. T. Goris, Eero P. Simoncelli

Nature Neuroscience, April 2019

Geodesics of learned representations

Olivier J. Hénaff, Eero P. Simoncelli

International Conference on Learning Representations (ICLR), May 2016

The local low-dimensionality of natural images

Olivier J. Hénaff, Johannes Ballé, Neil C. Rabinowitz, Eero P. Simoncelli

International Conference on Learning Representations (ICLR), May 2015 (Oral)

More info

Google Scholar / Twitter / LinkedIn