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February 14, 2026Journal of Japan Society for Fuzzy Theory and Intelligent InformaticsOpen Access

Knowledge Transfer from Human to Animal Pose Estimation Using Task Editing in Small-Scale Datasets

Harunobu ARIGA Yuki Shinomiya

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Key Points

Pose estimation models demonstrate potential in transferring knowledge from humans to animals.
Using task arithmetics with a small learning rate improves effectiveness in pose estimation tasks.
The approach employs difference vectors for joint estimation based on human and animal tasks.
Differences in annotation policies do not significantly impact accuracy in the model's performance.

Implication

Analysis reveals effective pose estimation in animals using limited data and task editing techniques.

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Cite This Study

ARIGA et al. (2026) studied this question.

synapsesocial.com/papers/69a7611ec6e9836116a2ebc5 https://doi.org/10.3156/jsoft.38.1_573

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