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README.md
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## Intended Use
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• Intended to be used for pose estimation of quadruped images taken from side-view. The model serves a better starting
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point than ImageNet weights in downstream datasets such as AP-10K.
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• Intended for academic and research professionals working in fields related to animal behavior, such as neuroscience
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and ecology.
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• Not suitable as a zeros-shot model for applications that require high keypiont precision, but can be fine-tuned with
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minimal data to reach human-level accuracy. Also not suitable for videos that look dramatically different from those
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we show in the paper.
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• Based on the known robustness issues of neural networks, the relevant factors include the lighting, contrast and
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resolution of the video frames. The present of objects might also cause false detections and erroneous keypoints.
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When two or more animals are extremely close, it could cause the top-down detectors to only detect only one animal,
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if used without further fine-tuning or with a method such as BUCTD (
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## Metrics
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• Mean Average Precision (mAP)
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## Intended Use
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• Intended to be used for pose estimation of quadruped images taken from side-view. The model serves a better starting
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point than ImageNet weights in downstream datasets such as AP-10K.
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+
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• Intended for academic and research professionals working in fields related to animal behavior, such as neuroscience
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and ecology.
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+
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• Not suitable as a zeros-shot model for applications that require high keypiont precision, but can be fine-tuned with
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minimal data to reach human-level accuracy. Also not suitable for videos that look dramatically different from those
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we show in the paper.
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+
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+
## Factors
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• Based on the known robustness issues of neural networks, the relevant factors include the lighting, contrast and
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resolution of the video frames. The present of objects might also cause false detections and erroneous keypoints.
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| 47 |
When two or more animals are extremely close, it could cause the top-down detectors to only detect only one animal,
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+
if used without further fine-tuning or with a method such as BUCTD (Zhou et al. 2023 ICCV).
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## Metrics
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• Mean Average Precision (mAP)
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