Maxime Oquab

5.8k total citations · 1 hit paper
9 papers, 2.1k citations indexed

About

Maxime Oquab is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Maxime Oquab has authored 9 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Cognitive Neuroscience. Recurrent topics in Maxime Oquab's work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers) and Functional Brain Connectivity Studies (2 papers). Maxime Oquab is often cited by papers focused on Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers) and Functional Brain Connectivity Studies (2 papers). Maxime Oquab collaborates with scholars based in France, United States and India. Maxime Oquab's co-authors include Josef Šivic, Léon Bottou, Ivan Laptev, David López-Paz, Jean-Rémi King, Romain Carron, Christian Bénar, Jean‐Michel Badier, Yair Lakretz and Stanislas Dehaene and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and arXiv (Cornell University).

In The Last Decade

Maxime Oquab

8 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

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

2014 2.0k citations Maxime Oquab, Léon Bottou et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Maxime Oquab France	4	1.2k	790	208	194	113	9	2.1k
Peng-Tao Jiang China	10	1.2k 1.0×	792 1.0×	266 1.3×	226 1.2×	153 1.4×	16	2.3k
Jia Deng China	5	1.2k 1.0×	778 1.0×	135 0.6×	192 1.0×	91 0.8×	14	1.9k
Camille Couprie France	12	1.4k 1.2×	555 0.7×	270 1.3×	151 0.8×	141 1.2×	23	2.3k
Michael S. Lew Netherlands	16	1.3k 1.1×	728 0.9×	208 1.0×	212 1.1×	169 1.5×	34	2.7k
Ard Oerlemans Netherlands	5	688 0.6×	518 0.7×	152 0.7×	179 0.9×	137 1.2×	12	1.8k
Zhongyue Zhang China	8	1.7k 1.5×	905 1.1×	368 1.8×	265 1.4×	160 1.4×	23	2.9k
Abhinav Shrivastava United States	20	2.1k 1.8×	1.3k 1.7×	272 1.3×	218 1.1×	130 1.2×	73	3.2k
Zhenda Xie China	7	1.4k 1.2×	786 1.0×	345 1.7×	239 1.2×	128 1.1×	10	2.4k
Tsung‐Yu Lin United States	9	1.3k 1.1×	679 0.9×	218 1.0×	130 0.7×	92 0.8×	13	2.0k

Countries citing papers authored by Maxime Oquab

Since Specialization

Citations

This map shows the geographic impact of Maxime Oquab's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maxime Oquab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxime Oquab more than expected).

Fields of papers citing papers by Maxime Oquab

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maxime Oquab. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maxime Oquab. The network helps show where Maxime Oquab may publish in the future.

Co-authorship network of co-authors of Maxime Oquab

This figure shows the co-authorship network connecting the top 25 collaborators of Maxime Oquab. A scholar is included among the top collaborators of Maxime Oquab based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maxime Oquab. Maxime Oquab is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Jose, Cijo, Théo Moutakanni, Timothée Darcet, et al.. (2025). DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment. 24905–24916. 1 indexed citations

2.

Lakretz, Yair, Valérie Chanoine, Maxime Oquab, et al.. (2023). Dimensionality and Ramping: Signatures of Sentence Integration in the Dynamics of Brains and Deep Language Models. Journal of Neuroscience. 43(29). 5350–5364. 16 indexed citations

3.

Touvron, Hugo, Matthieu Cord, Maxime Oquab, et al.. (2023). Co-training 2L Submodels for Visual Recognition. 11701–11710.

4.

King, Jean-Rémi, et al.. (2020). Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations. NeuroImage. 220. 117028–117028. 10 indexed citations

5.

Belghazi, Mohamed Ishmael, Maxime Oquab, & David López-Paz. (2019). Learning about an exponential amount of conditional distributions. Neural Information Processing Systems. 32. 13703–13714. 1 indexed citations

6.

Khalidov, Vasil, Maxime Oquab, Jérémy Rapin, & Olivier Teytaud. (2019). Consistent population control. 116–123. 2 indexed citations

7.

López-Paz, David & Maxime Oquab. (2016). Revisiting Classifier Two-Sample Tests for GAN Evaluation and Causal Discovery. arXiv (Cornell University). 3 indexed citations

8.

Oquab, Maxime, Léon Bottou, Ivan Laptev, & Josef Šivic. (2014). Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks. 1717–1724. 2011 indexed citations breakdown →

9.

Oquab, Maxime, Léon Bottou, Ivan Laptev, & Josef Šivic. (2014). Weakly supervised object recognition with convolutional neural networks. 38 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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