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Commit 4baa215d authored by Romain Guesdon's avatar Romain Guesdon
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Acknowledgments + intro + tabs

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...@@ -50,7 +50,21 @@ We used in our study three architectures: ...@@ -50,7 +50,21 @@ We used in our study three architectures:
We used for training and for inference the code provided by the authors in the three linked repositories. We used for training and for inference the code provided by the authors in the three linked repositories.
Weights of the trained model evaluated in our study can be found [here](). Weights of the trained model evaluated in our study can be found [here]().
More details about the training can be found in our paper. More details about the training can be found in our [paper](https://openaccess.thecvf.com/content/ICCV2021W/AVVision/papers/Guesdon_DriPE_A_Dataset_for_Human_Pose_Estimation_in_Real-World_Driving_ICCVW_2021_paper.pdf).
##### **HPE on the COCO 2017 validation set.**
AP OKS (\%) | AP | AP<sup>50</sup> | AP<sup>75</sup> | AP<sup>L</sup> | AR | AR<sup>50</sup> | AR<sup>75</sup> | AR<sup>L</sup>
:---- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
SBl | 72 | 92 | 80 | 77 | 76 | 93 | 82 | 80
MSPN | __77__ | 94 | 85 | 82 | __80__ | 95 | 87 | 85
RSN | 76 | 94 | 84 | 81 | 79 | 94 | 85 | 84
##### **HPE on the DriPE test set.**
AP OKS (\%) | AP | AP<sup>50</sup> | AP<sup>75</sup> | AP<sup>L</sup> | AR | AR<sup>50</sup> | AR<sup>75</sup> | AR<sup>L</sup>
:---- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
SBl | 75 | 99 | 91 | 75 | 81 | 99 | 94 | 81
MSPN | 81 | 99 | 97 | __81__ | 85 | 99 | 97 | __85__
RSN | 75 | 99 | 93 | 75 | 79 | 99 | 95 | 79
# Evaluation # Evaluation
Evaluation is performed using two metrics: Evaluation is performed using two metrics:
...@@ -95,8 +109,8 @@ If you use this dataset or code in your research, please cite the paper: ...@@ -95,8 +109,8 @@ If you use this dataset or code in your research, please cite the paper:
This work was supported by the Pack Ambition This work was supported by the Pack Ambition
Recherche 2019 funding of the French AURA Region in Recherche 2019 funding of the French AURA Region in
the context of the AutoBehave project. the context of the AutoBehave project.
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