d-li14/involution

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1310 stars · 175 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 involution neural operator from the CVPR 2021 paper 'Involution: Inverting the Inherence of Convolution for Visual Recognition'. It provides model files and configs built on OpenMMLab toolkits (mmclassification, mmdetection, mmsegmentation) with pre-trained checkpoints for ImageNet classification, COCO detection/segmentation, and Cityscapes segmentation.

Use cases

• replace convolution with involution in vision models
• train image classification models on ImageNet with involution backbones
• run object detection with involution-based ResNet on COCO
• semantic segmentation on Cityscapes using involution
• reproduce CVPR 2021 involution paper results
• compare involution against convolution and self-attention baselines

When to choose

• you want a more efficient alternative to convolution or self-attention in vision backbones
• you already use OpenMMLab toolkits like mmdetection or mmsegmentation
• you need pre-trained involution checkpoints for classification, detection, or segmentation research

When to avoid

• you need a maintained production library - the repo has not been updated since 2021
• your stack is TensorFlow, JAX, or non-OpenMMLab PyTorch frameworks
• you need plug-and-play layers without copying files into OpenMMLab codebases

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision deep-learning machine-learning python pytorch neural-operator involution cvpr2021 pretrained-models openmmlab image-classification object-detection semantic-segmentation research-code gpu

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