Methods › Computer Vision › Vision Transformers › PVT

Pyramid Vision Transformer

PVT

28 papers tagged archive 2025-07-28

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

PVT, or Pyramid Vision Transformer, is a type of vision transformer that utilizes a pyramid structure to make it an effective backbone for dense prediction tasks. Specifically it allows for more fine-grained inputs (4 x 4 pixels per patch) to be used, while simultaneously shrinking the sequence length of the Transformer as it deepens - reducing the computational cost. Additionally, a spatial-reduction attention (SRA) layer is used to further reduce the resource consumption when learning high-resolution features.

The entire model is divided into four stages, each of which is comprised of a patch embedding layer and a ℒᵢ-layer Transformer encoder. Following a pyramid structure, the output resolution of the four stages progressively shrinks from high (4-stride) to low (32-stride).

Source: Pyramid Vision Transformer: A Versatile Backbone for...

Papers archive 2025-07-28

28 shown of 28, 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 shown of 42 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
Object Detection6
Semantic Segmentation6
Image Classification3
Instance Segmentation3
Segmentation3
Inductive Bias2
Quantization2
Self-Supervised Learning2
image-classification2
object-detection2
3D Object Detection1
3D Part Segmentation1
3D Point Cloud Classification1
Action Recognition1
Autonomous Driving1
Computational Efficiency1
Continual Semantic Segmentation1
Data Augmentation1
Decoder1
Denoising1

Usage over time archive 2025-07-28

Papers per year tagged with PVT: 2021 to 2025, peak 10 10 0 2021: 4 papers 2021 2022: 5 papers 2022 2023: 10 papers 2023 2024: 7 papers 2024 2025: 2 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (28 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

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections