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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 39.8 36.1 model
R-50-FPN (d) Mask R-CNN 3x 7.2 0.806 5.4 40.1 36.4 model
R-101-FPN (d) Mask R-CNN 2x 9.9 0.970 4.8 41.5 37.0 model
R-101-FPN (d) Mask R-CNN 3x 9.9 0.970 4.8 41.6 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 40.0 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].
  • Memory, Train/Inf time is outdated.