| # You Only Look One-level Feature | |
| ## Introduction | |
| <!-- [ALGORITHM] --> | |
| ``` | |
| @inproceedings{chen2021you, | |
| title={You Only Look One-level Feature}, | |
| author={Chen, Qiang and Wang, Yingming and Yang, Tong and Zhang, Xiangyu and Cheng, Jian and Sun, Jian}, | |
| booktitle={IEEE Conference on Computer Vision and Pattern Recognition}, | |
| year={2021} | |
| } | |
| ``` | |
| ## Results and Models | |
| | Backbone | Style | Epoch | Lr schd | Mem (GB) | box AP | Config | Download | | |
| |:---------:|:-------:|:-------:|:-------:|:--------:|:------:|:------:|:--------:| | |
| | R-50-C5 | caffe | Y | 1x | 8.3 | 37.5 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/yolof/yolof_r50_c5_8x8_1x_coco.py) |[model](http://download.openmmlab.com/mmdetection/v2.0/yolof/yolof_r50_c5_8x8_1x_coco/yolof_r50_c5_8x8_1x_coco_20210425_024427-8e864411.pth) | [log](http://download.openmmlab.com/mmdetection/v2.0/yolof/yolof_r50_c5_8x8_1x_coco/yolof_r50_c5_8x8_1x_coco_20210425_024427.log.json) | | |
| **Note**: | |
| 1. We find that the performance is unstable and may fluctuate by about 0.3 mAP. mAP 37.4 ~ 37.7 is acceptable in YOLOF_R_50_C5_1x. Such fluctuation can also be found in the [original implementation](https://github.com/chensnathan/YOLOF). | |
| 2. In addition to instability issues, sometimes there are large loss fluctuations and NAN, so there may still be problems with this project, which will be improved subsequently. | |