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InfoResearchPeer-reviewed
Multimodal Human Pose Estimation: A Wi-Fi-Driven Approach With Adaptive Kernel Selection
- Published
- Record updated
Summary
HPE-Li++ is a Wi-Fi and camera-based approach to 3-D human pose estimation designed to run on resource-constrained devices. It combines a multibranch CNN with selective kernel attention, a Transformer module and a stacked autoencoder denoiser. On the MM-Fi and WiPose datasets it reports 85.58% and 94.27% PCK50, outperforming state-of-the-art methods, and keeps 80% PCK50 under AWGN noise with an error variance of 0.5.