The local low-dimensionality of natural images. - Olivier J. Hénaff; Johannes Ballé; Neil C. Rabinowitz; Eero P. Simoncelli (ICLR, 2015)

Geodesics of learned representations. - Olivier J. Hénaff; Eero P. Simoncelli (ICLR (Poster), 2016)

Data-Efficient Image Recognition with Contrastive Predictive Coding. - Olivier J. Hénaff; Aravind Srinivas; Jeffrey De Fauw; Ali Razavi; Carl Doersch; S. M. Ali Eslami; Aäron van den Oord (CoRR, 2019)

Data-Efficient Image Recognition with Contrastive Predictive Coding. - Olivier J. Hénaff (ICML, 2020)

Are we done with ImageNet? - Lucas Beyer; Olivier J. Hénaff; Alexander Kolesnikov 003; Xiaohua Zhai; Aäron van den Oord (CoRR, 2020)

Efficient Visual Pretraining with Contrastive Detection. - Olivier J. Hénaff; Skanda Koppula; Jean-Baptiste Alayrac; Aäron van den Oord; Oriol Vinyals; João Carreira 001 (ICCV, 2021)

Divide and Contrast: Self-supervised Learning from Uncurated Data. - Yonglong Tian; Olivier J. Hénaff; Aäron van den Oord (ICCV, 2021)

Object Discovery and Representation Networks. - Olivier J. Hénaff; Skanda Koppula; Evan Shelhamer; Daniel Zoran; Andrew Jaegle; Andrew Zisserman; João Carreira 001; Relja Arandjelovic (ECCV (27), 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 J. Hénaff; Matthew M. Botvinick; et al. (ICLR, 2022)

Hierarchical Perceiver. - João Carreira 001; Skanda Koppula; Daniel Zoran; Adrià Recasens; Catalin Ionescu; Olivier J. Hénaff; Evan Shelhamer; Relja Arandjelovic; Matthew M. Botvinick; Oriol Vinyals; Karen Simonyan; Andrew Zisserman; et al. (CoRR, 2022)

Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods. - Skanda Koppula; Yazhe Li; Evan Shelhamer; Andrew Jaegle; Nikhil Parthasarathy; Relja Arandjelovic; João Carreira 001; Olivier J. Hénaff (CoRR, 2022)

Self-supervised video pretraining yields strong image representations. - Nikhil Parthasarathy; S. M. Ali Eslami; João Carreira 001; Olivier J. Hénaff (CoRR, 2022)

Towards In-context Scene Understanding. - Ivana Balazevic; David Steiner 004; Nikhil Parthasarathy; Relja Arandjelovic; Olivier J. Hénaff (NeurIPS, 2023)

Self-supervised video pretraining yields robust and more human-aligned visual representations. - Nikhil Parthasarathy; S. M. Ali Eslami; João Carreira 001; Olivier J. Hénaff (NeurIPS, 2023)

Three ways to improve feature alignment for open vocabulary detection. - Relja Arandjelovic; Alex Andonian; Arthur Mensch; Olivier J. Hénaff; Jean-Baptiste Alayrac; Andrew Zisserman (CoRR, 2023)

Reflecting on the State of Rehearsal-Free Continual Learning with Pretrained Models. - Lukas Thede; Karsten Roth; Olivier J. Hénaff; Matthias Bethge; Zeynep Akata (CoLLAs, 2024)

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 (ECCV (17), 2024)

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model. - Karsten Roth; Lukas Thede; A. Sophia Koepke; Oriol Vinyals; Olivier J. Hénaff; Zeynep Akata (ICLR, 2024)

Memory Consolidation Enables Long-Context Video Understanding. - Ivana Balazevic; Yuge Shi; Pinelopi Papalampidi; Rahma Chaabouni 001; Skanda Koppula; Olivier J. Hénaff (ICML, 2024)

Data curation via joint example selection further accelerates multimodal learning. - Talfan Evans; Nikhil Parthasarathy; Hamza Merzic; Olivier J. Hénaff (NeurIPS, 2024)

A Practitioner's Guide to Real-World Continual Multimodal Pretraining. - Vishaal Udandarao; Karsten Roth; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Zeynep Akata; Matthias Bethge (NeurIPS, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

A Practitioner's Guide to Continual Multimodal Pretraining. - Karsten Roth; Vishaal Udandarao; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Matthias Bethge; Zeynep Akata (CoRR, 2024)

Layerwise complexity-matched learning yields an improved model of cortical area V2. - Nikhil Parthasarathy; Olivier J. Hénaff; Eero P. Simoncelli (Trans. Mach. Learn. Res., 2024)

Context-Aware Multimodal Pretraining. - Karsten Roth; Zeynep Akata; Dima Damen; Ivana Balazevic; Olivier J. Hénaff (CVPR, 2025)

Active Data Curation Effectively Distills Large-Scale Multimodal Models. - Vishaal Udandarao; Nikhil Parthasarathy; Muhammad Ferjad Naeem; Talfan Evans; Samuel Albanie; Federico Tombari; Yongqin Xian; Alessio Tonioni; Olivier J. Hénaff (CVPR, 2025)

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features. - Michael Tschannen; Alexey A. Gritsenko; Xiao Wang 038; Muhammad Ferjad Naeem; Ibrahim Alabdulmohsin; Nikhil Parthasarathy; Talfan Evans; Lucas Beyer; Ye Xia; Basil Mustafa; Olivier J. Hénaff; Jeremiah Harmsen; et al. (CoRR, 2025)