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) | Inf time (fps) | box AP | mask AP | Config | Download |
---|---|---|---|---|---|---|---|---|
R-50-FPN | caffe | 1x | 4.5 | 38.2 | 36.0 | config | model | log | |
R-50-FPN | caffe | 2x | - | - | 38.8 | 36.3 | config | model | log |
R-101-FPN | caffe | 1x | 6.5 | 40.4 | 37.6 | config | model | log | |
R-101-FPN | caffe | 2x | - | - | 41.1 | 38.1 | config | model | log |
R-X101-32x4d | pytorch | 2x | 7.9 | 11.0 | 41.8 | 38.7 | config | model | log |
R-X101-64x4d | pytorch | 1x | 11.0 | 8.0 | 43.0 | 39.5 | config | model | log |
R-X101-64x4d | pytorch | 2x | 11.0 | 8.0 | 42.6 | 39.5 | config | model | log |