README.md

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)	Train time (s/iter)	Inf time (fps)	box AP	mask AP	Download
R-50-FPN (d)	Mask R-CNN	2x	7.2	0.806	5.4	39.9	36.1	model
R-50-FPN (d)	Mask R-CNN	3x	7.2	0.806	5.4	40.2	36.5	model
R-101-FPN (d)	Mask R-CNN	2x	9.9	0.970	4.8	41.6	37.1	model
R-101-FPN (d)	Mask R-CNN	3x	9.9	0.970	4.8	41.7	37.3	model
R-50-FPN (c)	Mask R-CNN	2x	7.2	0.806	5.4	39.7	35.9	model
R-50-FPN (c)	Mask R-CNN	3x	7.2	0.806	5.4	40.1	36.2	model

Notes:

• (d) means pretrained model converted from Detectron, and (c) means the contributed model pretrained by @thangvubk.
• The 3x schedule is epoch [28, 34, 36].