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Maxime Oquab
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2020 – today
- 2024
- [j2]Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mido Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski:
DINOv2: Learning Robust Visual Features without Supervision. Trans. Mach. Learn. Res. 2024 (2024) - [c10]Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski:
Vision Transformers Need Registers. ICLR 2024 - [i13]Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon, Céline Hudelot, Armand Joulin, Yann LeCun, Matthew Muckley, Maxime Oquab, Marie-Pierre Revel, Maria Vakalopoulou:
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. CoRR abs/2405.01469 (2024) - [i12]Huy V. Vo, Vasil Khalidov, Timothée Darcet, Théo Moutakanni, Nikita Smetanin, Marc Szafraniec, Hugo Touvron, Camille Couprie, Maxime Oquab, Armand Joulin, Hervé Jégou, Patrick Labatut, Piotr Bojanowski:
Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach. CoRR abs/2405.15613 (2024) - [i11]Théo Moutakanni, Maxime Oquab, Marc Szafraniec, Maria Vakalopoulou, Piotr Bojanowski:
You Don't Need Data-Augmentation in Self-Supervised Learning. CoRR abs/2406.09294 (2024) - 2023
- [c9]Hugo Touvron, Matthieu Cord, Maxime Oquab, Piotr Bojanowski, Jakob Verbeek, Hervé Jégou:
Co-training 2L Submodels for Visual Recognition. CVPR 2023: 11701-11710 - [i10]Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. 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:
DINOv2: Learning Robust Visual Features without Supervision. CoRR abs/2304.07193 (2023) - [i9]Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski:
Vision Transformers Need Registers. CoRR abs/2309.16588 (2023) - 2022
- [i8]Maxime Oquab, Daniel Haziza, Ludovic Schwartz, Tao Xu, Katayoun Zand, Rui Wang, Peirong Liu, Camille Couprie:
Efficient conditioned face animation using frontally-viewed embedding. CoRR abs/2203.08765 (2022) - [i7]Hugo Touvron, Matthieu Cord, Maxime Oquab, Piotr Bojanowski, Jakob Verbeek, Hervé Jégou:
Co-training 2L Submodels for Visual Recognition. CoRR abs/2212.04884 (2022) - 2021
- [c8]Maxime Oquab, Pierre Stock, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie:
Low Bandwidth Video-Chat Compression Using Deep Generative Models. CVPR Workshops 2021: 2388-2397 - [i6]Yair Lakretz, Theo Desbordes, Jean-Rémi King, Benoît Crabbé, Maxime Oquab, Stanislas Dehaene:
Can RNNs learn Recursive Nested Subject-Verb Agreements? CoRR abs/2101.02258 (2021) - [i5]Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim:
Self-appearance-aided Differential Evolution for Motion Transfer. CoRR abs/2110.04658 (2021) - 2020
- [j1]Jean-Rémi King, François Charton, David Lopez-Paz, Maxime Oquab:
Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations. NeuroImage 220: 117028 (2020) - [i4]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:
Low Bandwidth Video-Chat Compression using Deep Generative Models. CoRR abs/2012.00328 (2020)
2010 – 2019
- 2019
- [c7]Vasil Khalidov, Maxime Oquab, Jérémy Rapin, Olivier Teytaud:
Consistent population control: generate plenty of points, but with a bit of resampling. FOGA 2019: 116-123 - [c6]Mohamed Ishmael Belghazi, Maxime Oquab, David Lopez-Paz:
Learning about an exponential amount of conditional distributions. NeurIPS 2019: 13703-13714 - [i3]Mohamed Ishmael Belghazi, Maxime Oquab, Yann LeCun, David Lopez-Paz:
Learning about an exponential amount of conditional distributions. CoRR abs/1902.08401 (2019) - 2018
- [b1]Maxime Oquab:
Convolutional neural networks: towards less supervision for visual recognition. (Réseaux de neurones à convolution: vers moins de supervision pour la reconnaissance visuelle). École Normale Supérieure, Paris, France, 2018 - 2017
- [c5]Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab:
Geometrical Insights for Implicit Generative Modeling. Braverman Readings in Machine Learning 2017: 229-268 - [c4]David Lopez-Paz, Maxime Oquab:
Revisiting Classifier Two-Sample Tests. ICLR (Poster) 2017 - [i2]Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab:
Geometrical Insights for Implicit Generative Modeling. CoRR abs/1712.07822 (2017) - 2016
- [c3]Vadim Kantorov, Maxime Oquab, Minsu Cho, Ivan Laptev:
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization. ECCV (5) 2016: 350-365 - [i1]Vadim Kantorov, Maxime Oquab, Minsu Cho, Ivan Laptev:
ContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization. CoRR abs/1609.04331 (2016) - 2015
- [c2]Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic:
Is object localization for free? - Weakly-supervised learning with convolutional neural networks. CVPR 2015: 685-694 - 2014
- [c1]Maxime Oquab, Léon Bottou, Ivan Laptev, Josef Sivic:
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks. CVPR 2014: 1717-1724
Coauthor Index
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last updated on 2024-08-10 01:27 CEST by the dblp team
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