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Code for training 'CoupleNet: Coupling Global Structure with Local Parts for Object Detection' in ICCV 2017
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README.md

CoupleNet

CoupleNet: Coupling Global Structure with Local Parts for Object Detection

The Code is modified from py-R-FCN, please follow the procedure in it to prepare the training data and testing data. Using the default hyperparameters and iterations, you can achieve a mAP around 81.7%.

Main results

  training data test data mAP@0.5 time/img(ms)
CoupleNet, ResNet-101** VOC 07+12 VOC 07 test 81.7% 102
CoupleNet, ResNet-101 VOC 07+12 VOC 07 test 82.1% 122
CoupleNet, ResNet-101 VOC 07++12 VOC 12 test 80.4% 122

**: without adding context.

  training data test data mAP@[0.5:0.95] time/img(ms)
CoupleNet, ResNet-101 COCO 2014 trainval COCO test dev 34.4% 122

VOC 0712 model (trained on VOC 07+12, mAP 81.7%)

Citing CoupleNet

If you find CoupleNet useful in your research, please consider citing:

@article{zhu2017couplenet,
    title={CoupleNet: Coupling Global Structure with Local Parts for Object Detection},
    author={Zhu, Yousong and Zhao, Chaoyang and Wang, Jinqiao and Zhao, Xu and Wu, Yi and Lu, Hanqing},
    journal={arXiv preprint arXiv:1708.02863},
    year={2017}
}
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