AI RESEARCH
GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation
arXiv CS.CV
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ArXi:2605.13151v1 Announce Type: new Category-agnostic pose estimation (CAPE) aims to localize keypoints on query images from arbitrary categories, using only a few annotated examples for guidance. Recent approaches either treat keypoints as isolated entities or rely on manually defined skeleton priors, which are costly to annotate and inherently inflexible across diverse categories. Such oversimplification limits the model's capacity to capture instance-wise structural cues critical for accurate pixel-level localization.