Maxime Oquab
Impact in
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Human Pose and Action Recognition
- Artificial Intelligence top 1%
- Domain Adaptation and Few-Shot Learning
Papers in
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- Domain Adaptation and Few-Shot Learning 3
- Adversarial Robustness in Machine Learning 2
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- Advanced Image and Video Retrieval Techniques 4
- Advanced Neural Network Applications 4
- Multimodal Machine Learning Applications 2
- Co-authors
- Ivan Laptev (3 shared papers)Léon Bottou (2 shared papers)Josef Šivic (2 shared papers)Minsu Cho (1 shared paper)David López-Paz (3 shared papers)Jean-Rémi King (2 shared papers)Valérie Chanoine (1 shared paper)J. Badier (1 shared paper)
- Journals
- NeuroImage (1 paper)Journal of Neuroscience (1 paper)Lecture notes in computer science (1 paper)arXiv (Cornell University) (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- FranceUnited StatesBurundi
In The Last Decade
Maxime Oquab
9 papers receiving 2.5k citations
Maxime Oquab's Hit Papers
Peers
Comparison fields: 5 of 153
- Computer Vision and Pattern Recognition 1.5k
- Artificial Intelligence 1.0k
- Media Technology 255
- Signal Processing 119
- Radiology, Nuclear Medicine and Imaging 206
Countries citing papers authored by Maxime Oquab
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
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-authors
The 25 scholars most cited alongside Maxime Oquab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks Hit paper breakdown → | 2014 | 2278 |
| 2 | 2016 | 197 | |
| 3 | Weakly supervised object recognition with convolutional neural networks | 2014 | 38 |
| 4 | 2023 | 16 | |
| 5 | 2020 | 10 | |
| 6 | Revisiting Classifier Two-Sample Tests for GAN Evaluation and Causal Discovery | 2016 | 3 |
| 7 | 2025 | 3 | |
| 8 | 2019 | 2 | |
| 9 | Learning about an exponential amount of conditional distributions | 2019 | 1 |
| 10 | 2023 | 1 |
About Maxime Oquab
Maxime Oquab is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Statistical and Nonlinear Physics and Signal Processing, having authored 10 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Adversarial Robustness in Machine Learning (2 papers), Functional Brain Connectivity Studies (2 papers), Multimodal Machine Learning Applications (2 papers), Robotics and Sensor-Based Localization (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Artificial Intelligence (1.0k citations), Media Technology (255 citations), Signal Processing (119 citations) and Radiology, Nuclear Medicine and Imaging (206 citations). Maxime Oquab has collaborated with scholars based in France, United States and Burundi. Frequent co-authors include Ivan Laptev, Léon Bottou, Josef Šivic, Minsu Cho, David López-Paz, Jean-Rémi King, Valérie Chanoine, J. Badier, Christian Bénar and Yair Lakretz. Their work appears in journals such as NeuroImage, Journal of Neuroscience, Lecture notes in computer science, arXiv (Cornell University) and Neural Information Processing Systems.
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.