Animal Models

Deep high-resolution representation learning for human pose estimation

Introduction

@inproceedings{sun2019deep,
  title={Deep high-resolution representation learning for human pose estimation},
  author={Sun, Ke and Xiao, Bin and Liu, Dong and Wang, Jingdong},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={5693--5703},
  year={2019}
}

Results and models

2d Animal Landmark Detection

Results on Horse-10 test set

Set	Arch	Input Size	PCK@0.3	NME	ckpt	log
split1	pose_hrnet_w32	256x256	0.951	0.122	ckpt	log
split2	pose_hrnet_w32	256x256	0.949	0.116	ckpt	log
split3	pose_hrnet_w32	256x256	0.939	0.153	ckpt	log
split1	pose_hrnet_w48	256x256	0.973	0.095	ckpt	log
split2	pose_hrnet_w48	256x256	0.969	0.101	ckpt	log
split3	pose_hrnet_w48	256x256	0.961	0.128	ckpt	log

Results on MacaquePose with ground-truth detection bounding boxes

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_hrnet_w32	256x192	0.814	0.953	0.918	0.851	0.969	ckpt	log
pose_hrnet_w48	256x192	0.818	0.963	0.917	0.855	0.971	ckpt	log

Results on ATRW validation set

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_hrnet_w32	256x256	0.912	0.973	0.959	0.938	0.985	ckpt	log
pose_hrnet_w48	256x256	0.911	0.972	0.946	0.937	0.985	ckpt	log

Results on AnimalPose validation set (1117 instances)

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_hrnet_w32	256x256	0.736	0.959	0.832	0.775	0.966	ckpt	log
pose_hrnet_w48	256x256	0.911	0.972	0.946	0.937	0.985	ckpt	log

Simple baselines for human pose estimation and tracking

Introduction

@inproceedings{xiao2018simple,
  title={Simple baselines for human pose estimation and tracking},
  author={Xiao, Bin and Wu, Haiping and Wei, Yichen},
  booktitle={Proceedings of the European conference on computer vision (ECCV)},
  pages={466--481},
  year={2018}
}

Results and models

2d Animal Landmark Detection

Results on Horse-10 test set

Set	Arch	Input Size	PCK@0.3	NME	ckpt	log
split1	pose_resnet_50	256x256	0.956	0.113	ckpt	log
split2	pose_resnet_50	256x256	0.954	0.111	ckpt	log
split3	pose_resnet_50	256x256	0.946	0.129	ckpt	log
split1	pose_resnet_101	256x256	0.958	0.115	ckpt	log
split2	pose_resnet_101	256x256	0.955	0.115	ckpt	log
split3	pose_resnet_101	256x256	0.946	0.126	ckpt	log
split1	pose_resnet_152	256x256	0.969	0.105	ckpt	log
split2	pose_resnet_152	256x256	0.970	0.103	ckpt	log
split3	pose_resnet_152	256x256	0.957	0.131	ckpt	log

Results on MacaquePose with ground-truth detection bounding boxes

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_resnet_50	256x192	0.799	0.952	0.919	0.837	0.964	ckpt	log
pose_resnet_101	256x192	0.790	0.953	0.908	0.828	0.967	ckpt	log
pose_resnet_152	256x192	0.794	0.951	0.915	0.834	0.968	ckpt	log

Results on Vinegar Fly test set

Arch	Input Size	PCK@0.2	AUC	EPE	ckpt	log
pose_resnet_50	192x192	0.996	0.910	2.00	ckpt	log
pose_resnet_101	192x192	0.996	0.912	1.95	ckpt	log
pose_resnet_152	192x192	0.997	0.917	1.78	ckpt	log

Results on Desert Locust test set

Arch	Input Size	PCK@0.2	AUC	EPE	ckpt	log
pose_resnet_50	160x160	0.999	0.899	2.27	ckpt	log
pose_resnet_101	160x160	0.999	0.907	2.03	ckpt	log
pose_resnet_152	160x160	1.000	0.926	1.48	ckpt	log

Results on Grévy’s Zebra test set

Arch	Input Size	PCK@0.2	AUC	EPE	ckpt	log
pose_resnet_50	160x160	1.000	0.914	1.86	ckpt	log
pose_resnet_101	160x160	1.000	0.916	1.82	ckpt	log
pose_resnet_152	160x160	1.000	0.921	1.66	ckpt	log

Results on ATRW validation set

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_resnet_50	256x256	0.900	0.973	0.932	0.929	0.985	ckpt	log
pose_resnet_101	256x256	0.898	0.973	0.936	0.927	0.985	ckpt	log
pose_resnet_152	256x256	0.896	0.973	0.931	0.927	0.985	ckpt	log

Results on AnimalPose validation set (1117 instances)

Arch	Input Size	AP	AP50	AP75	AR	AR50	ckpt	log
pose_resnet_50	256x256	0.688	0.945	0.772	0.733	0.952	ckpt	log
pose_resnet_101	256x256	0.696	0.948	0.785	0.737	0.954	ckpt	log
pose_resnet_152	256x256	0.709	0.948	0.797	0.749	0.951	ckpt	log