# msracver/Deformable-ConvNets

Deformable Convolutional Networks

Repository: https://github.com/msracver/Deformable-ConvNets
Canonical: https://ross.abutalabs.com/products/deformable-convnets
Language: Python
License: MIT
License Family: permissive
Last push: 2021-09-27T01:43:43+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3407, "days_push": 1802, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4121, forks 948 (observed 2026-08-28T04:08:35.965285+00:00)

## What it is
Official MXNet implementation of Deformable Convolutional Networks (ICCV 2017) and R-FCN, including deformable convolution and ROI pooling operators. It provides training and testing code for object detection and segmentation models such as Deformable FPN and Deformable R-FCN.

## Use cases
- implement deformable convolution layers in detection models
- reproduce COCO object detection results with Deformable FPN
- train Deformable R-FCN with Soft NMS
- run Deformable ConvNets v2 operators
- research learnable spatial sampling in CNNs

## When to choose
- you need the official reference implementation of deformable convolutions on MXNet
- you want to reproduce the Deformable ConvNets or R-FCN papers
- you need the corrected DCNv2 operator with boundary handling

## When to avoid
- you want a maintained PyTorch implementation - use mmdetection instead
- you need a production-ready detection framework
- you don't work with MXNet or legacy CUDA builds

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, computer-vision, image-processing
- domain: computer-vision, deep-learning, machine-learning
- platform: python, windows
- tags: deformable-convolution, object-detection, mxnet, rfcn, instance-segmentation, research-code, linux

## Member repositories
- msracver/Deformable-ConvNets (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:35.965285+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:23:06.683167+00:00, confidence not recorded.
  - readme: https://github.com/msracver/Deformable-ConvNets (fetched 2026-08-28T04:08:35.965285+00:00, sha 928c668b0aef)
- Data as of 2026-08-30T08:39:29.467469+00:00.