Methods › General › Output Functions › ADRM
Adaptive Dynamic Recursive Mapping
ADRM
Introduced by Yong Su et al. in Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Adaptive Dynamic Recursive Mapping (ADRM)
sₜ₊₁=ψ_α(sₜ)=sₜ+α (sₜ-sₜ²), α∈[-1,1].
- α>0 amplifies evidence for abnormality
- α<0 suppresses false positives
- α=0 leaves the score unchanged
Here, sₜ is the anomaly score at step t, and the adaptive decision parameter α is learned jointly with the backbone detector. By recursively mapping the score trajectory, ADRM stabilises detector outputs, magnifies truly anomalous segments, and damps noisy spikes, yielding more reliable video-level anomaly detection under weak supervision and heterogeneous federated settings.
Papers archive 2025-07-28
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Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping 13 Jun 2025 · 1 repository
Tasks archive 2025-07-28
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Usage over time archive 2025-07-28
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