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DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

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DetectoRS

News

[06/30/2020] DetectoRS is now officially supported by MMDetection. A huge thanks to @xvjiarui, @ZwwWayne and @hellock for helping migrating the code.

[06/15/2020] We have released the implementation of DetectoRS based on mmdetection-v2 in the branch mmdetv2, which allows more detectors to use RFP and SAC.

Introduction

This repo holds the code for DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution. The project is based on mmdetection codebase. Please refer to mmdetection readme for installation and running scripts. The code is tested with PyTorch 1.4.0. It may not run with other versions. See conda_env.md for the versions of all the packages.

Main Results on COCO test-dev

Method Backbone Config Model Box AP Mask AP
DetectoRS ResNet-50 File Link Download 51.3 44.4
DetectoRS ResNeXt-101-32x4d File Link Download 53.3 45.8

Citing DetectoRS

If you think DetectoRS is useful in your project, please consider citing us.

@article{detectors,
  title={DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution},
  author={Qiao, Siyuan and Chen, Liang-Chieh and Yuille, Alan},
  journal={arXiv preprint arXiv:2006.02334},
  year={2020}
}

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DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

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  • Python 86.4%
  • Cuda 8.0%
  • C++ 5.5%
  • Other 0.1%