mirror of https://github.com/open-mmlab/mmpose
17 KiB
17 KiB
RTMPose (arXiv'2023)
@misc{https://doi.org/10.48550/arxiv.2303.07399,
doi = {10.48550/ARXIV.2303.07399},
url = {https://arxiv.org/abs/2303.07399},
author = {Jiang, Tao and Lu, Peng and Zhang, Li and Ma, Ningsheng and Han, Rui and Lyu, Chengqi and Li, Yining and Chen, Kai},
keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose},
publisher = {arXiv},
year = {2023},
copyright = {Creative Commons Attribution 4.0 International}
}
RTMDet (arXiv'2022)
@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}
}
COCO (ECCV'2014)
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
booktitle={European conference on computer vision},
pages={740--755},
year={2014},
organization={Springer}
}
Human-Art (CVPR'2023)
@inproceedings{ju2023humanart,
title={Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes},
author={Ju, Xuan and Zeng, Ailing and Jianan, Wang and Qiang, Xu and Lei, Zhang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
year={2023}}
Results on Human-Art validation dataset with detector having human AP of 56.2 on Human-Art validation dataset
Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
---|---|---|---|---|---|---|---|---|
rtmpose-t-coco | 256x192 | 0.161 | 0.283 | 0.154 | 0.221 | 0.373 | ckpt | log |
rtmpose-t-humanart-coco | 256x192 | 0.249 | 0.395 | 0.256 | 0.323 | 0.485 | ckpt | log |
rtmpose-s-coco | 256x192 | 0.199 | 0.328 | 0.198 | 0.261 | 0.418 | ckpt | log |
rtmpose-s-humanart-coco | 256x192 | 0.311 | 0.462 | 0.323 | 0.381 | 0.540 | ckpt | log |
rtmpose-m-coco | 256x192 | 0.239 | 0.372 | 0.243 | 0.302 | 0.455 | ckpt | log |
rtmpose-m-humanart-coco | 256x192 | 0.355 | 0.503 | 0.377 | 0.417 | 0.568 | ckpt | log |
rtmpose-l-coco | 256x192 | 0.260 | 0.393 | 0.267 | 0.323 | 0.472 | ckpt | log |
rtmpose-l-humanart-coco | 256x192 | 0.378 | 0.521 | 0.399 | 0.442 | 0.584 | ckpt | log |
Results on Human-Art validation dataset with ground-truth bounding-box
Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
---|---|---|---|---|---|---|---|---|
rtmpose-t-coco | 256x192 | 0.444 | 0.725 | 0.453 | 0.488 | 0.750 | ckpt | log |
rtmpose-t-humanart-coco | 256x192 | 0.655 | 0.872 | 0.720 | 0.693 | 0.890 | ckpt | log |
rtmpose-s-coco | 256x192 | 0.480 | 0.739 | 0.498 | 0.521 | 0.763 | ckpt | log |
rtmpose-s-humanart-coco | 256x192 | 0.698 | 0.893 | 0.768 | 0.732 | 0.903 | ckpt | log |
rtmpose-m-coco | 256x192 | 0.532 | 0.765 | 0.563 | 0.571 | 0.789 | ckpt | log |
rtmpose-m-humanart-coco | 256x192 | 0.728 | 0.895 | 0.791 | 0.759 | 0.906 | ckpt | log |
rtmpose-l-coco | 256x192 | 0.564 | 0.789 | 0.602 | 0.599 | 0.808 | ckpt | log |
rtmpose-l-humanart-coco | 256x192 | 0.753 | 0.905 | 0.812 | 0.783 | 0.915 | ckpt | log |
Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset
Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
---|---|---|---|---|---|---|---|---|
rtmpose-t-coco | 256x192 | 0.682 | 0.883 | 0.759 | 0.736 | 0.920 | ckpt | log |
rtmpose-t-humanart-coco | 256x192 | 0.665 | 0.875 | 0.739 | 0.721 | 0.916 | ckpt | log |
rtmpose-s-coco | 256x192 | 0.716 | 0.892 | 0.789 | 0.768 | 0.929 | ckpt | log |
rtmpose-s-humanart-coco | 256x192 | 0.706 | 0.888 | 0.780 | 0.759 | 0.928 | ckpt | log |
rtmpose-m-coco | 256x192 | 0.746 | 0.899 | 0.817 | 0.795 | 0.935 | ckpt | log |
rtmpose-m-humanart-coco | 256x192 | 0.725 | 0.892 | 0.795 | 0.775 | 0.929 | ckpt | log |
rtmpose-l-coco | 256x192 | 0.758 | 0.906 | 0.826 | 0.806 | 0.942 | ckpt | log |
rtmpose-l-humanart-coco | 256x192 | 0.748 | 0.901 | 0.816 | 0.796 | 0.938 | ckpt | log |
Results on COCO val2017 with ground-truth bounding box
Arch | Input Size | AP | AP50 | AP75 | AR | AR50 | ckpt | log |
---|---|---|---|---|---|---|---|---|
rtmpose-t-humanart-coco | 256x192 | 0.679 | 0.895 | 0.755 | 0.710 | 0.907 | ckpt | log |
rtmpose-s-humanart-coco | 256x192 | 0.725 | 0.916 | 0.798 | 0.753 | 0.925 | ckpt | log |
rtmpose-m-humanart-coco | 256x192 | 0.744 | 0.916 | 0.818 | 0.770 | 0.930 | ckpt | log |
rtmpose-l-humanart-coco | 256x192 | 0.770 | 0.927 | 0.840 | 0.794 | 0.939 | ckpt | log |