AMAR uses a transformer with learnable query embeddings for set-based prediction of concurrent activities from composite Wi-Fi CSI, combined with edge feature extraction and vector quantization for bandwidth-efficient deployment.
Multitrack: Multi-user tracking and activity recog- nition using commodity WiFi,
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AMAR: Lightweight Attention-Based Multi-User Activity Recognition from Wi-Fi CSI
AMAR uses a transformer with learnable query embeddings for set-based prediction of concurrent activities from composite Wi-Fi CSI, combined with edge feature extraction and vector quantization for bandwidth-efficient deployment.