Grid R-CNN
Introduction
@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
2xhere indicates 25 epochs.