AI RESEARCH
Towards Robust and Realistic Human Pose Estimation via WiFi Signals
arXiv CS.CV
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ArXi:2501.09411v3 Announce Type: replace Robust WiFi-based human pose estimation (HPE) is a challenging task that bridges discrete and subtle WiFi signals to human skeletons. We revisit this problem and reveal two critical yet overlooked issues: 1) cross-domain gap, i.e., due to significant discrepancies in pose distributions between source and target domains; and 2) structural fidelity gap, i.e., predicted skeletal poses manifest distorted topology, usually with misplaced joints and disproportionate bone lengths.