RTMDet (ArXiv 2022)
```bibtex
@misc{lyu2022rtmdet,
title={RTMDet: An Empirical Study of Designing Real-Time Object Detectors},
author={Chengqi Lyu and Wenwei Zhang and Haian Huang and Yue Zhou and Yudong Wang and Yanyi Liu and Shilong Zhang and Kai Chen},
year={2022},
eprint={2212.07784},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
WFLW (CVPR'2018)
```bibtex
@inproceedings{wu2018look,
title={Look at boundary: A boundary-aware face alignment algorithm},
author={Wu, Wayne and Qian, Chen and Yang, Shuo and Wang, Quan and Cai, Yici and Zhou, Qiang},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={2129--2138},
year={2018}
}
```
Results on WFLW dataset
The model is trained on WFLW train.
| Arch | Input Size | NME | ckpt | log |
| :------------------------------------------------------------- | :--------: | :--: | :------------------------------------------------------------: | :------------------------------------------------------------: |
| [pose_rtmpose_m](/configs/face_2d_keypoint/rtmpose/wflw/rtmpose-m_8xb64-60e_wflw-256x256.py) | 256x256 | 4.01 | [ckpt](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-wflw_pt-aic-coco_60e-256x256-dc1dcdcf_20230228.pth) | [log](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-wflw_pt-aic-coco_60e-256x256-dc1dcdcf_20230228.json) |