A semantic drift calibration method combining weighted mean shift compensation, Mahalanobis-distance covariance matching, and patch-token self-distillation improves class-incremental learning accuracy on ImageNet-R, ImageNet-A, CUB-200, and CIFAR-100.
D., Twardowski, B., and van de Weijer, J
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Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
A semantic drift calibration method combining weighted mean shift compensation, Mahalanobis-distance covariance matching, and patch-token self-distillation improves class-incremental learning accuracy on ImageNet-R, ImageNet-A, CUB-200, and CIFAR-100.