Maxime Oquab

According to our database, Maxime Oquab authored at least 19 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Vision Transformers Need Registers.

Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski

CoRR, 2023

DINOv2: Learning Robust Visual Features without Supervision.

Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski

CoRR, 2023

Co-training 2L Submodels for Visual Recognition.

Hugo Touvron, Matthieu Cord, Maxime Oquab, Piotr Bojanowski, Jakob Verbeek, Hervé Jégou

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Co-training 2^L Submodels for Visual Recognition.

Hugo Touvron, Matthieu Cord, Maxime Oquab, Piotr Bojanowski, Jakob Verbeek, Hervé Jégou

CoRR, 2022

Efficient conditioned face animation using frontally-viewed embedding.

Maxime Oquab, Daniel Haziza, Ludovic Schwartz, Tao Xu, Katayoun Zand, Rui Wang, Peirong Liu, Camille Couprie

CoRR, 2022

2021

Self-appearance-aided Differential Evolution for Motion Transfer.

Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim

CoRR, 2021

Can RNNs learn Recursive Nested Subject-Verb Agreements?

Yair Lakretz, Theo Desbordes, Jean-Rémi King, Benoît Crabbé, Maxime Oquab, Stanislas Dehaene

CoRR, 2021

Low Bandwidth Video-Chat Compression Using Deep Generative Models.

Maxime Oquab, Pierre Stock, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations.

Jean-Rémi King, François Charton, David Lopez-Paz, Maxime Oquab

NeuroImage, 2020

Low Bandwidth Video-Chat Compression using Deep Generative Models.

Maxime Oquab, Pierre Stock, Oran Gafni, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie

CoRR, 2020

2019

Learning about an exponential amount of conditional distributions.

Mohamed Ishmael Belghazi, Maxime Oquab, Yann LeCun, David Lopez-Paz

CoRR, 2019

Learning about an exponential amount of conditional distributions.

Mohamed Ishmael Belghazi, Maxime Oquab, David Lopez-Paz

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Consistent population control: generate plenty of points, but with a bit of resampling.

Vasil Khalidov, Maxime Oquab, Jérémy Rapin, Olivier Teytaud

Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

2018

Convolutional neural networks: towards less supervision for visual recognition. (Réseaux de neurones à convolution: vers moins de supervision pour la reconnaissance visuelle).

Maxime Oquab

PhD thesis, 2018

2017

Revisiting Classifier Two-Sample Tests.

David Lopez-Paz, Maxime Oquab

Proceedings of the 5th International Conference on Learning Representations, 2017

Geometrical Insights for Implicit Generative Modeling.

Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab

Proceedings of the Braverman Readings in Machine Learning. Key Ideas from Inception to Current State, 2017

2016

ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization.

Vadim Kantorov, Maxime Oquab, Minsu Cho, Ivan Laptev

Proceedings of the Computer Vision - ECCV 2016, 2016

2015

Is object localization for free? - Weakly-supervised learning with convolutional neural networks.

Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks.

Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014