CharlesShang/DCNv2

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1323 stars · 395 forks observed · 2026-08-28

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

A PyTorch implementation of Deformable Convolutional Networks v2 (DCNv2), providing CUDA/CPU operators for deformable convolution as a drop-in layer. It is an adaptation of the official MXNet Deformable-ConvNets operator for PyTorch 1.x.

Use cases

• add deformable convolution layers to a PyTorch model
• implement DCNv2 for object detection backbones
• build instance or semantic segmentation models with deformable convolutions
• run gradient checks for custom CUDA convolution operators
• port the official Deformable-ConvNets operator to PyTorch 1.x

When to choose

• you need deformable convolution in PyTorch with GPU acceleration
• you want a battle-tested DCNv2 operator with passing gradient checks
• you are reproducing detection/segmentation papers that rely on DCNv2

When to avoid

• you use PyTorch 2.x or newer where torchvision ships torchvision.ops.deform_conv2d
• you need a maintained library with active bug fixes
• you need deformable attention (DCNv3/v4) rather than deformable convolution

Facets

library · maturity maintenance

machine-learning deep-learning image-processing deep-learning computer-vision machine-learning python cpp windows pytorch deformable-convolution cnn cuda-extension object-detection gpu linux macos

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