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Mask Scoring R-CNN

Introduction

@inproceedings{huang2019msrcnn,
    title={Mask Scoring R-CNN},
    author={Zhaojin Huang and Lichao Huang and Yongchao Gong and Chang Huang and Xinggang Wang},
    booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
    year={2019},
}

Results and Models

Backbone style Lr schd Mem (GB) Train time (s/iter) Inf time (fps) box AP mask AP Download
R-50-FPN caffe 1x 4.3 0.537 10.1 37.4 35.5 model
R-50-FPN caffe 2x - - - 38.2 35.9 model
R-101-FPN caffe 1x 6.2 0.682 9.1 39.8 37.2 model
R-101-FPN caffe 2x - - - 40.7 37.8 model
R-X101-32x4d pytorch 2x 7.6 0.844 8.0 41.7 38.5 model
R-X101-64x4d pytorch 1x 10.5 1.214 6.4 42.0 39.1 model
R-X101-64x4d pytorch 2x - - - 42.2 38.9 model