Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation

arXiv:2401.08328v2 Announce Type: replace
Abstract: Recent test-time adaptation methods heavily rely on nuanced adjustments of batch normalization (BN) parameters. However, one critical assumption often goes overlooked: that of independently and identically distributed (i.i.d.) test batches with respect to unknown labels. This oversight leads to skewed BN statistics and undermines the reliability of the model under non-i.i.d. scenarios. To tackle this challenge, this paper presents a novel method termed 'Un-Mixing Test-Time Normalization Statistics' (UnMix-TNS). Our method re-calibrates the statistics for each …

arxiv correlation cs.cv normalization statistics temporal test type