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researcher

Maxime Oquab

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.LG1
same name
  • Maxime Oquab — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedContextLocNet: Context-Aware Deep Network Models for Weakly Supervised Localization

43 citations · 52 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2024★ 4 cited

DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment

Cijo Jose, Théo Moutakanni, Dahyun Kang +11

Self-supervised visual foundation models produce powerful embeddings that achieve remarkable performance on a wide range of downstream tasks. However, unlike vision-language models…

cs.LG2024★ 5 cited

Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach

Huy V. Vo, Vasil Khalidov, Timothée Darcet +10

Self-supervised features are the cornerstone of modern machine learning systems. They are typically pre-trained on data collections whose construction and curation typically requir…

cs.CV2016★ 43 cited

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

Vadim Kantorov, Maxime Oquab, Minsu Cho +1

We aim to localize objects in images using image-level supervision only. Previous approaches to this problem mainly focus on discriminative object regions and often fail to locate…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.