Methods › Computer Vision › Vision Transformers › LeVIT

LeVIT

2 papers tagged archive 2025-07-28

Introduced by Ben Graham et al. in LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference

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

LeVIT is a hybrid neural network for fast inference image classification. LeViT is a stack of transformer blocks, with pooling steps to reduce the resolution of the activation maps as in classical convolutional architectures. This replaces the uniform structure of a Transformer by a pyramid with pooling, similar to the LeNet architecture

PaperSource

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

5 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
Anomaly Detection1
CPU1
General Classification1
Image Classification1
image-classification1

Usage over time archive 2025-07-28

Papers per year tagged with LeVIT: 2021 to 2023, peak 1 1 0 2021: 1 paper 2021 2022: 0 papers 2022 2023: 1 paper 2023
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

Vision Transformers

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