Corpus ID: 237352914

AP-10K: A Benchmark for Animal Pose Estimation in the Wild

@article{Yu2021AP10KAB,
  title={AP-10K: A Benchmark for Animal Pose Estimation in the Wild},
  author={Hang Yu and Yufei Xu and Jing Zhang and Wei Zhao and Ziyu Guan and Dacheng Tao},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.12617}
}
  • Hang Yu, Yufei Xu, +3 authors D. Tao
  • Published 2021
  • Computer Science
  • ArXiv
Accurate animal pose estimation is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife conservation. Previous works only focus on specific animals while ignoring the diversity of animal species, limiting the generalization ability. In this paper, we propose AP-10K, the first large-scale benchmark for general animal pose estimation, to facilitate the research in animal pose estimation. AP-10K consists of 10,015… Expand

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References

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This paper proposed a novel cross-domain adaptation method to transform the animal pose knowledge from labeled animal classes to unlabeled animal classes, and uses the modest animal pose dataset to adapt learned knowledge to multiple animals species. Expand
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