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Grid R-CNN

Introduction

[ALGORITHM]

@inproceedings{lu2019grid,
  title={Grid r-cnn},
  author={Lu, Xin and Li, Buyu and Yue, Yuxin and Li, Quanquan and Yan, Junjie},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2019}
}

@article{lu2019grid,
  title={Grid R-CNN Plus: Faster and Better},
  author={Lu, Xin and Li, Buyu and Yue, Yuxin and Li, Quanquan and Yan, Junjie},
  journal={arXiv preprint arXiv:1906.05688},
  year={2019}
}

Results and Models

Backbone Lr schd Mem (GB) Inf time (fps) box AP Config Download
R-50 2x 5.1 15.0 40.4 config model | log
R-101 2x 7.0 12.6 41.5 config model | log
X-101-32x4d 2x 8.3 10.8 42.9 config model | log
X-101-64x4d 2x 11.3 7.7 43.0 config model | log

Notes:

  • All models are trained with 8 GPUs instead of 32 GPUs in the original paper.
  • The warming up lasts for 1 epoch and 2x here indicates 25 epochs.