
..
coco_wholebody_hand	[update]RTMposeを用いた検出機能の実装	1 year ago
freihand2d	[update]RTMposeを用いた検出機能の実装	1 year ago
onehand10k	[update]RTMposeを用いた検出機能の実装	1 year ago
rhd2d	[update]RTMposeを用いた検出機能の実装	1 year ago
README.md	[update]RTMposeを用いた検出機能の実装	1 year ago

Top-down heatmap-based pose estimation

Top-down methods divide the task into two stages: object detection, followed by single-object pose estimation given object bounding boxes. Instead of estimating keypoint coordinates directly, the pose estimator will produce heatmaps which represent the likelihood of being a keypoint, following the paradigm introduced in Simple Baselines for Human Pose Estimation and Tracking.

Results and Models

COCO-WholeBody-Hand Dataset

Results on COCO-WholeBody-Hand val set

Model	Input Size	PCK@0.2	AUC	EPE	Details and Download
HRNetv2-w18+Dark	256x256	0.814	0.840	4.37	hrnetv2_dark_coco_wholebody_hand.md
HRNetv2-w18	256x256	0.813	0.840	4.39	hrnetv2_coco_wholebody_hand.md
HourglassNet	256x256	0.804	0.835	4.54	hourglass_coco_wholebody_hand.md
SCNet-50	256x256	0.803	0.834	4.55	scnet_coco_wholebody_hand.md
ResNet-50	256x256	0.800	0.833	4.64	resnet_coco_wholebody_hand.md
LiteHRNet-18	256x256	0.795	0.830	4.77	litehrnet_coco_wholebody_hand.md
MobileNet-v2	256x256	0.795	0.829	4.77	mobilenetv2_coco_wholebody_hand.md

FreiHand Dataset

Results on FreiHand val & test set

Model	Input Size	PCK@0.2	AUC	EPE	Details and Download
ResNet-50	224x224	0.999	0.868	3.27	resnet_freihand2d.md

OneHand10K Dataset

Results on OneHand10K val set

Model	Input Size	PCK@0.2	AUC	EPE	Details and Download
HRNetv2-w18+Dark	256x256	0.990	0.572	23.96	hrnetv2_dark_onehand10k.md
HRNetv2-w18+UDP	256x256	0.990	0.571	23.88	hrnetv2_udp_onehand10k.md
HRNetv2-w18	256x256	0.990	0.567	24.26	hrnetv2_onehand10k.md
ResNet-50	256x256	0.989	0.555	25.16	resnet_onehand10k.md
MobileNet-v2	256x256	0.986	0.537	28.56	mobilenetv2_onehand10k.md

RHD Dataset

Results on RHD test set

Model	Input Size	PCK@0.2	AUC	EPE	Details and Download
HRNetv2-w18+Dark	256x256	0.992	0.903	2.18	hrnetv2_dark_rhd2d.md
HRNetv2-w18+UDP	256x256	0.992	0.902	2.19	hrnetv2_udp_rhd2d.md
HRNetv2-w18	256x256	0.992	0.902	2.21	hrnetv2_rhd2d.md
ResNet-50	256x256	0.991	0.898	2.32	resnet_rhd2d.md
MobileNet-v2	256x256	0.985	0.883	2.79	mobilenetv2_rhd2d.md