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cs.CV2025
An uncertainty-aware framework for data-efficient multi-view animal pose estimation
Lenny Aharon, Keemin Lee, Karan Sikka +4
Multi-view pose estimation is essential for quantifying animal behavior in scientific research, yet current methods struggle to achieve accurate tracking with limited labeled data…
cs.CV2024
A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms
Ari Blau, Evan S Schaffer, Neeli Mishra +4
Action segmentation of behavioral videos is the process of labeling each frame as belonging to one or more discrete classes, and is a crucial component of many studies that investi…