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Siyuan Qiao authored
* fix init bug in rfp

* add comments about the init bug in rfp

* update model link

* update performance

Co-authored-by: default avatarJiarui XU <xvjiarui0826@gmail.com>
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DetectoRS

Introduction

We provide the config files for DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution.

@article{qiao2020detectors,
  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}
}

Results and Models

DetectoRS includes two major components:

  • Recursive Feature Pyramid (RFP).
  • Switchable Atrous Convolution (SAC).

They can be used independently. Combining them together results in DetectoRS. The results on COCO 2017 val are shown in the below table.

Method Detector Lr schd Mem (GB) Inf time (fps) box AP mask AP Download
RFP Cascade + ResNet-50 1x 7.5 - 44.8 model | log
SAC Cascade + ResNet-50 1x 5.6 - 45.0 model | log
DetectoRS Cascade + ResNet-50 1x 9.9 - 47.4 model | log
RFP HTC + ResNet-50 1x 11.2 - 46.6 40.9 model | log
SAC HTC + ResNet-50 1x 9.3 - 46.4 40.9 model | log
DetectoRS HTC + ResNet-50 1x 13.6 - 49.1 42.6 model | log

Note: This is a re-implementation based on MMDetection-V2. The original implementation is based on MMDetection-V1.