Methods › Computer Vision › Convolutional Neural Networks › MultiGrain

MultiGrain

2 papers tagged archive 2025-07-28

Introduced by Maxim Berman et al. in MultiGrain: a unified image embedding for classes and instances

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

MultiGrain is a type of image model that learns a single embedding for classes, instances and copies. In other words, it is a convolutional neural network that is suitable for both image classification and instance retrieval. We learn MultiGrain by jointly training an image embedding for multiple tasks. The resulting representation is compact and can outperform narrowly-trained embeddings. The learned embedding output incorporates different levels of granularity.

PaperSourceSee Code · facebookresearch/multigrain

Papers archive 2025-07-28

2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

9 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Classification1
Data Augmentation1
General Classification1
Image Classification1
Image Retrieval1
Object1
Physical Simulations1
Retrieval1
image-classification1

Usage over time archive 2025-07-28

Papers per year tagged with MultiGrain: 2019 to 2024, peak 1 1 0 2019: 1 paper 2019 2020: 0 papers 2020 2021: 0 papers 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Convolutional Neural Networks

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