Lite-HRNet: A Lightweight High-Resolution Network
Introduction
@inproceedings{Yulitehrnet21,
title={Lite-HRNet: A Lightweight High-Resolution Network},
author={Yu, Changqian and Xiao, Bin and Gao, Changxin and Yuan, Lu and Zhang, Lei and Sang, Nong and Wang, Jingdong},
booktitle={CVPR},
year={2021}
}
Results and models
Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset
| Arch |
Input Size |
#Params |
FLOPs |
AP |
AP50 |
AP75 |
AR |
AR50 |
| Lite-HRNet-18 |
256x192 |
1.1M |
205.2M |
0.648 |
0.867 |
0.730 |
0.712 |
0.911 |
| Lite-HRNet-18 |
384x288 |
1.1M |
461.6M |
0.676 |
0.878 |
0.750 |
0.737 |
0.921 |
| Lite-HRNet-30 |
256x192 |
1.8M |
319.2M |
0.672 |
0.880 |
0.750 |
0.733 |
0.922 |
| Lite-HRNet-30 |
384x288 |
1.8M |
717.8M |
0.704 |
0.887 |
0.777 |
0.762 |
0.928 |
Results on MPII val set.
| Arch |
Input Size |
#Params |
FLOPs |
Mean |
Mean@0.1 |
| Lite-HRNet-18 |
256x256 |
1.1M |
273.4M |
0.854 |
0.295 |
| Lite-HRNet-30 |
256x256 |
1.8M |
425.3M |
0.870 |
0.313 |
