Demo-Maker/modules/rtmpose/configs/hand_3d_keypoint/internet/interhand3d/internet_interhand3d.md at main

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.