Hand 3D Keypoint¶
Interhand3d Dataset¶
Internet + Internet on Interhand3d¶
InterNet (ECCV'2020)
@InProceedings{Moon_2020_ECCV_InterHand2.6M,
author = {Moon, Gyeongsik and Yu, Shoou-I and Wen, He and Shiratori, Takaaki and Lee, Kyoung Mu},
title = {InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2020}
}
ResNet (CVPR'2016)
@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}
}
InterHand2.6M (ECCV'2020)
@InProceedings{Moon_2020_ECCV_InterHand2.6M,
author = {Moon, Gyeongsik and Yu, Shoou-I and Wen, He and Shiratori, Takaaki and Lee, Kyoung Mu},
title = {InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2020}
}
Results on InterHand2.6M val & test set
Train Set | Set | Arch | Input Size | MPJPE-single | MPJPE-interacting | MPJPE-all | MRRPE | APh | ckpt | log |
---|---|---|---|---|---|---|---|---|---|---|
All | test(H+M) | InterNet_resnet_50 | 256x256 | 9.69 | 13.72 | 11.86 | 29.27 | 0.99 | ckpt | log |
All | val(M) | InterNet_resnet_50 | 256x256 | 11.30 | 15.57 | 13.36 | 32.15 | 0.98 | ckpt | log |
All | test(H+M) | InterNet_resnet_50* | 256x256 | 9.47 | 13.40 | 11.59 | 29.28 | 0.99 | ckpt | log |
All | val(M) | InterNet_resnet_50* | 256x256 | 11.22 | 15.23 | 13.16 | 31.73 | 0.98 | ckpt | log |
Models with * are trained in MMPose 0.x. The checkpoints and logs are only for validation.