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configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-256x192.py
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configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-384x288.py
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configs/body_2d_keypoint/rtmpose/body8/rtmpose-m_8xb256-210e_body8-256x192.py
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configs/body_2d_keypoint/rtmpose/body8/rtmpose-s_8xb256-210e_body8-256x192.py
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configs/body_2d_keypoint/rtmpose/body8/rtmpose-t_8xb256-210e_body8-256x192.py
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<!-- [ALGORITHM] --> | ||
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<details> | ||
<summary align="right"><a href="https://link.springer.com/chapter/10.1007/978-3-030-58580-8_27">RTMPose (arXiv'2023)</a></summary> | ||
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```bibtex | ||
@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} | ||
} | ||
``` | ||
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</details> | ||
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<!-- [BACKBONE] --> | ||
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<details> | ||
<summary align="right"><a href="https://arxiv.org/abs/2212.07784">RTMDet (arXiv'2022)</a></summary> | ||
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```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} | ||
} | ||
``` | ||
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</details> | ||
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<!-- [DATASET] --> | ||
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<details> | ||
<summary align="right"><a href="https://link.springer.com/chapter/10.1007/978-3-319-10602-1_48">COCO (ECCV'2014)</a></summary> | ||
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```bibtex | ||
@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} | ||
} | ||
``` | ||
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</details> | ||
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- Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset. | ||
- `*` denotes model trained on 7 public datasets: | ||
- [AI Challenger](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#aic) | ||
- [MS COCO](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#coco) | ||
- [CrowdPose](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#crowdpose) | ||
- [MPII](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#mpii) | ||
- [sub-JHMDB](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#sub-jhmdb-dataset) | ||
- [Halpe](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_wholebody_keypoint.html#halpe) | ||
- [PoseTrack18](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#posetrack18) | ||
- `Body8` denotes the addition of the [OCHuman](https://mmpose.readthedocs.io/en/latest/dataset_zoo/2d_body_keypoint.html#ochuman) dataset, in addition to the 7 datasets mentioned above, for evaluation. | ||
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| Config | Input Size | AP<sup><br>(COCO) | [email protected]<sup><br>(Body8) | AUC<sup><br>(Body8) | EPE<sup><br>(Body8) | Params(M) | FLOPS(G) | Download | | ||
| :--------------------------------------------: | :--------: | :---------------: | :---------------------: | :-----------------: | :-----------------: | :-------: | :------: | :-----------------------------------------------: | | ||
| [RTMPose-t\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-t_8xb256-210e_body8-256x192.py) | 256x192 | 65.9 | 91.44 | 63.18 | 19.45 | 3.34 | 0.36 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-t_simcc-body7_pt-body7_420e-256x192-026a1439_20230504.pth) | | ||
| [RTMPose-s\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-s_8xb256-210e_body8-256x192.py) | 256x192 | 69.7 | 92.45 | 65.15 | 17.85 | 5.47 | 0.68 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-s_simcc-body7_pt-body7_420e-256x192-acd4a1ef_20230504.pth) | | ||
| [RTMPose-m\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-m_8xb256-210e_body8-256x192.py) | 256x192 | 74.9 | 94.25 | 68.59 | 15.12 | 13.59 | 1.93 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.pth) | | ||
| [RTMPose-l\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-256x192.py) | 256x192 | 76.7 | 95.08 | 70.14 | 13.79 | 27.66 | 4.16 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-body7_pt-body7_420e-256x192-4dba18fc_20230504.pth) | | ||
| [RTMPose-m\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-m_8xb256-210e_body8-384x288.py) | 384x288 | 76.6 | 94.64 | 70.38 | 13.98 | 13.72 | 4.33 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-body7_pt-body7_420e-384x288-65e718c4_20230504.pth) | | ||
| [RTMPose-l\*](/configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-384x288.py) | 384x288 | 78.3 | 95.36 | 71.58 | 13.08 | 27.79 | 9.35 | [Model](https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-body7_pt-body7_420e-384x288-3f5a1437_20230504.pth) | |
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Collections: | ||
- Name: RTMPose | ||
Paper: | ||
Title: "RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose" | ||
URL: https://arxiv.org/abs/2303.07399 | ||
README: https://github.com/open-mmlab/mmpose/blob/main/projects/rtmpose/README.md | ||
Models: | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-t_8xb256-210e_body8-256x192.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: &id001 | ||
- RTMPose | ||
Training Data: &id002 | ||
- AI Challenger | ||
- COCO | ||
- CrowdPose | ||
- MPII | ||
- sub-JHMDB | ||
- Halpe | ||
- PoseTrack18 | ||
Name: rtmpose-t_8xb256-210e_body8-256x192 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.659 | ||
[email protected]: 0.914 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-t_simcc-body7_pt-body7_420e-256x192-026a1439_20230504.pth | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-s_8xb256-210e_body8-256x192.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: *id001 | ||
Training Data: *id002 | ||
Name: rtmpose-s_8xb256-210e_body8-256x192 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.697 | ||
[email protected]: 0.925 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-s_simcc-body7_pt-body7_420e-256x192-acd4a1ef_20230504.pth | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-m_8xb256-210e_body8-256x192.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: *id001 | ||
Training Data: *id002 | ||
Name: rtmpose-m_8xb256-210e_body8-256x192 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.749 | ||
[email protected]: 0.943 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-body7_pt-body7_420e-256x192-e48f03d0_20230504.pth | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-256x192.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: *id001 | ||
Training Data: *id002 | ||
Name: rtmpose-l_8xb256-210e_body8-256x192 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.767 | ||
[email protected]: 0.951 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-body7_pt-body7_420e-256x192-4dba18fc_20230504.pth | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-m_8xb256-210e_body8-384x288.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: *id001 | ||
Training Data: *id002 | ||
Name: rtmpose-m_8xb256-210e_body8-384x288 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.766 | ||
[email protected]: 0.946 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-body7_pt-body7_420e-384x288-65e718c4_20230504.pth | ||
- Config: configs/body_2d_keypoint/rtmpose/body8/rtmpose-l_8xb256-210e_body8-384x288.py | ||
In Collection: RTMPose | ||
Metadata: | ||
Architecture: *id001 | ||
Training Data: *id002 | ||
Name: rtmpose-l_8xb256-210e_body8-384x288 | ||
Results: | ||
- Dataset: Body8 | ||
Metrics: | ||
AP: 0.783 | ||
[email protected]: 0.964 | ||
Task: Body 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-l_simcc-body7_pt-body7_420e-384x288-3f5a1437_20230504.pth |
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configs/face_2d_keypoint/topdown_regression/wflw/resnet_wingloss_wflw.md
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<!-- [ALGORITHM] --> | ||
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<details> | ||
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2014/html/Toshev_DeepPose_Human_Pose_2014_CVPR_paper.html">DeepPose (CVPR'2014)</a></summary> | ||
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```bibtex | ||
@inproceedings{toshev2014deeppose, | ||
title={Deeppose: Human pose estimation via deep neural networks}, | ||
author={Toshev, Alexander and Szegedy, Christian}, | ||
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, | ||
pages={1653--1660}, | ||
year={2014} | ||
} | ||
``` | ||
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</details> | ||
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<!-- [BACKBONE] --> | ||
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<details> | ||
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2016/html/He_Deep_Residual_Learning_CVPR_2016_paper.html">ResNet (CVPR'2016)</a></summary> | ||
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```bibtex | ||
@inproceedings{he2016deep, | ||
title={Deep residual learning for image recognition}, | ||
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian}, | ||
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, | ||
pages={770--778}, | ||
year={2016} | ||
} | ||
``` | ||
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</details> | ||
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<!-- [ALGORITHM] --> | ||
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<details> | ||
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2018/html/Feng_Wing_Loss_for_CVPR_2018_paper.html">Wingloss (CVPR'2018)</a></summary> | ||
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```bibtex | ||
@inproceedings{feng2018wing, | ||
title={Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks}, | ||
author={Feng, Zhen-Hua and Kittler, Josef and Awais, Muhammad and Huber, Patrik and Wu, Xiao-Jun}, | ||
booktitle={Computer Vision and Pattern Recognition (CVPR), 2018 IEEE Conference on}, | ||
year={2018}, | ||
pages ={2235-2245}, | ||
organization={IEEE} | ||
} | ||
``` | ||
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</details> | ||
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<!-- [DATASET] --> | ||
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<details> | ||
<summary align="right"><a href="http://openaccess.thecvf.com/content_cvpr_2018/html/Wu_Look_at_Boundary_CVPR_2018_paper.html">WFLW (CVPR'2018)</a></summary> | ||
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```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} | ||
} | ||
``` | ||
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</details> | ||
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Results on WFLW dataset | ||
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The model is trained on WFLW train set. | ||
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| Model | Input Size | NME | ckpt | log | | ||
| :-------------------------------------------------------------- | :--------: | :--: | :------------------------------------------------------------: | :-----------------------------------------------------------: | | ||
| [ResNet-50+WingLoss](/configs/face_2d_keypoint/topdown_regression/wflw/td-reg_res50_wingloss_8xb64-210e_wflw-256x256.py) | 256x256 | 4.67 | [ckpt](https://download.openmmlab.com/mmpose/face/deeppose/deeppose_res50_wflw_256x256_wingloss-f82a5e53_20210303.pth) | [log](https://download.openmmlab.com/mmpose/face/deeppose/deeppose_res50_wflw_256x256_wingloss_20210303.log.json) | |
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configs/face_2d_keypoint/topdown_regression/wflw/resnet_wingloss_wflw.yml
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Models: | ||
- Config: configs/face_2d_keypoint/topdown_regression/wflw/td-reg_res50_wingloss_8xb64-210e_wflw-256x256.py | ||
In Collection: ResNet | ||
Metadata: | ||
Architecture: | ||
- DeepPose | ||
- ResNet | ||
- WingLoss | ||
Training Data: WFLW | ||
Name: td-reg_res50_wingloss_8xb64-210e_wflw-256x256 | ||
Results: | ||
- Dataset: WFLW | ||
Metrics: | ||
NME: 4.67 | ||
Task: Face 2D Keypoint | ||
Weights: https://download.openmmlab.com/mmpose/face/deeppose/deeppose_res50_wflw_256x256_wingloss-f82a5e53_20210303.pth |
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