Group Normalization
Introduction
@inproceedings{wu2018group,
title={Group Normalization},
author={Wu, Yuxin and He, Kaiming},
booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
year={2018}
}
Results and Models
| Backbone | model | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
|---|---|---|---|---|---|---|---|---|
| R-50-FPN (d) | Mask R-CNN | 2x | 7.1 | 11.0 | 40.2 | 36.4 | config | model | log |
| R-50-FPN (d) | Mask R-CNN | 3x | 7.1 | - | 40.5 | 36.7 | config | model | log |
| R-101-FPN (d) | Mask R-CNN | 2x | 9.9 | 9.0 | 41.9 | 37.6 | config | model | log |
| R-101-FPN (d) | Mask R-CNN | 3x | 9.9 | 42.1 | 38.0 | config | model | log | |
| R-50-FPN (c) | Mask R-CNN | 2x | 7.1 | 10.9 | 40.0 | 36.1 | config | model | log |
| R-50-FPN (c) | Mask R-CNN | 3x | 7.1 | - | 40.1 | 36.2 | config | model | log |
Notes:
- (d) means pretrained model converted from Detectron, and (c) means the contributed model pretrained by @thangvubk.
- The
3xschedule is epoch [28, 34, 36]. - Memory, Train/Inf time is outdated.