# Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training

## Introduction

<!-- [ALGORITHM] -->

```
@article{DynamicRCNN,
    author = {Hongkai Zhang and Hong Chang and Bingpeng Ma and Naiyan Wang and Xilin Chen},
    title = {Dynamic {R-CNN}: Towards High Quality Object Detection via Dynamic Training},
    journal = {arXiv preprint arXiv:2004.06002},
    year = {2020}
}
```

## Results and Models

| Backbone  | Style   | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
|:---------:|:-------:|:-------:|:--------:|:--------------:|:------:|:------:|:--------:|
| 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](http://download.openmmlab.com/mmdetection/v2.0/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x/dynamic_rcnn_r50_fpn_1x-62a3f276.pth) &#124; [log](http://download.openmmlab.com/mmdetection/v2.0/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x/dynamic_rcnn_r50_fpn_1x_20200618_095048.log.json) |