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π RuView: WiFi DensePose turns commodity WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection — all without a single pixel of video.

0 0 97 Rust

docs(adr-150): few-shot adaptation resolves the cross-subject frontier

Decisive result: 50 labeled frames/subject of in-room calibration ->
72.2% (reaches SOTA), 200 -> 76.1%, 1000 -> 78.3%. Few-shot target
adaptation dominates source volume (+24 subjects bought +6pt; 200 target
frames bought +12.4pt). Re-scopes the deployment story: ship a ~30s on-site
calibration, not a mass corpus. Foundation encoder's role shifts to making
that calibration cheaper. Supersedes the earlier data-bound pessimism.

Co-Authored-By: claude-flow <ruv@ruv.net>
R
ruv committed
898aaef053317027c399dfde7597f6a17c96f809
Parent: 70bf9e4