Face Density as a Proxy for Data Complexity: Quantifying the Hardness of Instance Count
This paper establishes instance density as a quantifiable, intrinsic driver of data complexity by demonstrating that machine learning performance degrades monotonically with increasing face counts and that models trained on low-density data fail to generalize to denser scenarios due to systematic under-counting biases.