Beyond the Fold: Quantifying Split-Level Noise and the Case for Leave-One-Dataset-Out AU Evaluation
Beyond the Fold: Quantifying Split-Level Noise and the Case for Leave-One-Dataset-Out AU Evaluation explores A novel evaluation protocol for facial action unit detection that quantifies noise and improves robustness, revealing that many reported gains may be artifacts of the testing method.. Commercial viability score: 3/10 in AI Evaluation & Benchmarking.
Updated 6 hours ago
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