Methods › Computer Vision › Vision Transformers › MViT

Multiscale Vision Transformer

MViT

9 papers tagged archive 2025-07-28

Introduced by Haoqi Fan et al. in Multiscale Vision Transformers

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

Multiscale Vision Transformer, or MViT, is a transformer architecture for modeling visual data such as images and videos. Unlike conventional transformers, which maintain a constant channel capacity and resolution throughout the network, Multiscale Transformers have several channel-resolution scale stages. Starting from the input resolution and a small channel dimension, the stages hierarchically expand the channel capacity while reducing the spatial resolution. This creates a multiscale pyramid of features with early layers operating at high spatial resolution to model simple low-level visual information, and deeper layers at spatially coarse, but complex, high-dimensional features.

PaperSource

Papers archive 2025-07-28

9 shown of 9, 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

20 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
Action Recognition3
Video Recognition3
Action Classification2
Benchmarking2
Image Classification2
Object2
Object Detection2
Class-agnostic Object Detection1
EEG1
Instance Segmentation1
Object Proposal Generation1
Open World Object Detection1
Prediction1
Seizure prediction1
Temporal Action Localization1
Time Series1
Video Classification1
Video Understanding1
image-classification1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with MViT: 2021 to 2023, peak 4 4 0 2021: 4 papers 2021 2022: 2 papers 2022 2023: 3 papers 2023
Papers per year the archive tags with this method, by the paper's archive date (9 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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