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 |
Download |
| R-50-FPN |
caffe |
1x |
4.5 |
|
38.2 |
36.0 |
model | log |
| R-50-FPN |
caffe |
2x |
- |
- |
38.8 |
36.3 |
model | log |
| R-101-FPN |
caffe |
1x |
6.5 |
|
40.4 |
37.6 |
model | log |
| R-101-FPN |
caffe |
2x |
- |
- |
41.1 |
38.1 |
model | log |
| R-X101-32x4d |
pytorch |
2x |
7.9 |
11.0 |
41.8 |
38.7 |
model | log |
| R-X101-64x4d |
pytorch |
1x |
11.0 |
8.0 |
43.0 |
39.5 |
model | log |
| R-X101-64x4d |
pytorch |
2x |
11.0 |
8.0 |
42.6 |
39.5 |
model | log |