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README.md 1.1 kB

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  1. # Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training
  2. ## Introduction
  3. <!-- [ALGORITHM] -->
  4. ```
  5. @article{DynamicRCNN,
  6. author = {Hongkai Zhang and Hong Chang and Bingpeng Ma and Naiyan Wang and Xilin Chen},
  7. title = {Dynamic {R-CNN}: Towards High Quality Object Detection via Dynamic Training},
  8. journal = {arXiv preprint arXiv:2004.06002},
  9. year = {2020}
  10. }
  11. ```
  12. ## Results and Models
  13. | Backbone | Style | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
  14. |:---------:|:-------:|:-------:|:--------:|:--------------:|:------:|:------:|:--------:|
  15. | R-50 | pytorch | 1x | 3.8 | | 38.9 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x/dynamic_rcnn_r50_fpn_1x-62a3f276.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x/dynamic_rcnn_r50_fpn_1x_20200618_095048.log.json) |

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