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Animalpose Dataset


Topdown Heatmap + Hrnet on Animalpose

HRNet (CVPR'2019)
@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}
}
Animal-Pose (ICCV'2019)
@InProceedings{Cao_2019_ICCV,
    author = {Cao, Jinkun and Tang, Hongyang and Fang, Hao-Shu and Shen, Xiaoyong and Lu, Cewu and Tai, Yu-Wing},
    title = {Cross-Domain Adaptation for Animal Pose Estimation},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
    month = {October},
    year = {2019}
}

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 0.737 0.959 0.823 0.778 0.962 ckpt log

Topdown Heatmap + Resnet on Animalpose

SimpleBaseline2D (ECCV'2018)
@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}
}
Animal-Pose (ICCV'2019)
@InProceedings{Cao_2019_ICCV,
    author = {Cao, Jinkun and Tang, Hongyang and Fang, Hao-Shu and Shen, Xiaoyong and Lu, Cewu and Tai, Yu-Wing},
    title = {Cross-Domain Adaptation for Animal Pose Estimation},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
    month = {October},
    year = {2019}
}

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



Atrw Dataset


Topdown Heatmap + Resnet on Atrw

SimpleBaseline2D (ECCV'2018)
@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}
}
ATRW (ACM MM'2020)
@inproceedings{li2020atrw,
  title={ATRW: A Benchmark for Amur Tiger Re-identification in the Wild},
  author={Li, Shuyuan and Li, Jianguo and Tang, Hanlin and Qian, Rui and Lin, Weiyao},
  booktitle={Proceedings of the 28th ACM International Conference on Multimedia},
  pages={2590--2598},
  year={2020}
}

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

Topdown Heatmap + Hrnet on Atrw

HRNet (CVPR'2019)
@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}
}
ATRW (ACM MM'2020)
@inproceedings{li2020atrw,
  title={ATRW: A Benchmark for Amur Tiger Re-identification in the Wild},
  author={Li, Shuyuan and Li, Jianguo and Tang, Hanlin and Qian, Rui and Lin, Weiyao},
  booktitle={Proceedings of the 28th ACM International Conference on Multimedia},
  pages={2590--2598},
  year={2020}
}

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



Fly Dataset


Topdown Heatmap + Resnet on Fly

SimpleBaseline2D (ECCV'2018)
@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}
}
Vinegar Fly (Nature Methods'2019)
@article{pereira2019fast,
  title={Fast animal pose estimation using deep neural networks},
  author={Pereira, Talmo D and Aldarondo, Diego E and Willmore, Lindsay and Kislin, Mikhail and Wang, Samuel S-H and Murthy, Mala and Shaevitz, Joshua W},
  journal={Nature methods},
  volume={16},
  number={1},
  pages={117--125},
  year={2019},
  publisher={Nature Publishing Group}
}

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



Horse10 Dataset


Topdown Heatmap + Resnet on Horse10

SimpleBaseline2D (ECCV'2018)
@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}
}
Horse-10 (WACV'2021)
@inproceedings{mathis2021pretraining,
  title={Pretraining boosts out-of-domain robustness for pose estimation},
  author={Mathis, Alexander and Biasi, Thomas and Schneider, Steffen and Yuksekgonul, Mert and Rogers, Byron and Bethge, Matthias and Mathis, Mackenzie W},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={1859--1868},
  year={2021}
}

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

Topdown Heatmap + Hrnet on Horse10

HRNet (CVPR'2019)
@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}
}
Horse-10 (WACV'2021)
@inproceedings{mathis2021pretraining,
  title={Pretraining boosts out-of-domain robustness for pose estimation},
  author={Mathis, Alexander and Biasi, Thomas and Schneider, Steffen and Yuksekgonul, Mert and Rogers, Byron and Bethge, Matthias and Mathis, Mackenzie W},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={1859--1868},
  year={2021}
}

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



Locust Dataset


Topdown Heatmap + Resnet on Locust

SimpleBaseline2D (ECCV'2018)
@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}
}
Desert Locust (Elife'2019)
@article{graving2019deepposekit,
  title={DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning},
  author={Graving, Jacob M and Chae, Daniel and Naik, Hemal and Li, Liang and Koger, Benjamin and Costelloe, Blair R and Couzin, Iain D},
  journal={Elife},
  volume={8},
  pages={e47994},
  year={2019},
  publisher={eLife Sciences Publications Limited}
}

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



Macaque Dataset


Topdown Heatmap + Resnet on Macaque

SimpleBaseline2D (ECCV'2018)
@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}
}
MacaquePose (bioRxiv'2020)
@article{labuguen2020macaquepose,
  title={MacaquePose: A novel ‘in the wild’macaque monkey pose dataset for markerless motion capture},
  author={Labuguen, Rollyn and Matsumoto, Jumpei and Negrete, Salvador and Nishimaru, Hiroshi and Nishijo, Hisao and Takada, Masahiko and Go, Yasuhiro and Inoue, Ken-ichi and Shibata, Tomohiro},
  journal={bioRxiv},
  year={2020},
  publisher={Cold Spring Harbor Laboratory}
}

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

Topdown Heatmap + Hrnet on Macaque

HRNet (CVPR'2019)
@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}
}
MacaquePose (bioRxiv'2020)
@article{labuguen2020macaquepose,
  title={MacaquePose: A novel ‘in the wild’macaque monkey pose dataset for markerless motion capture},
  author={Labuguen, Rollyn and Matsumoto, Jumpei and Negrete, Salvador and Nishimaru, Hiroshi and Nishijo, Hisao and Takada, Masahiko and Go, Yasuhiro and Inoue, Ken-ichi and Shibata, Tomohiro},
  journal={bioRxiv},
  year={2020},
  publisher={Cold Spring Harbor Laboratory}
}

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



Zebra Dataset


Topdown Heatmap + Resnet on Zebra

SimpleBaseline2D (ECCV'2018)
@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}
}
Grévy’s Zebra (Elife'2019)
@article{graving2019deepposekit,
  title={DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning},
  author={Graving, Jacob M and Chae, Daniel and Naik, Hemal and Li, Liang and Koger, Benjamin and Costelloe, Blair R and Couzin, Iain D},
  journal={Elife},
  volume={8},
  pages={e47994},
  year={2019},
  publisher={eLife Sciences Publications Limited}
}

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
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