@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},
}
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 |