whai362/PVT

Health v2 · maintenance only

Adoption not part of the score

1900 stars · 252 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of the Pyramid Vision Transformer (PVTv1 and PVTv2) model series, providing pretrained backbone networks for computer vision. It includes model weights and configs for image classification, object detection, and semantic segmentation tasks.

Use cases

• use a vision transformer backbone for image classification on ImageNet
• pretrained PVT backbone for object detection with Mask R-CNN or RetinaNet
• semantic segmentation models using PVT as encoder
• compare PVTv2 against Swin Transformer backbones
• extract multi-scale features from images for downstream vision tasks
• fine-tune a pyramid vision transformer on custom datasets

When to choose

• you need a well-tested transformer backbone for detection or segmentation with mmdetection/mmsegsupport
• you want pretrained ImageNet weights for a pyramid-style vision transformer
• you are reproducing or building on the PVT papers

When to avoid

• you need a general-purpose training framework rather than specific backbone models
• you require a CNN backbone like ResNet instead of transformers
• you need actively maintained code with recent updates, as development has slowed

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision deep-learning machine-learning python vision-transformer backbone pyramid-vision-transformer object-detection semantic-segmentation image-classification pretrained-models pytorch

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