Rethinking BCE Loss for Multi-Label Image Recognition with Fine-Tuning
Class-wise Covariance Regularization is proposed, which aligns the predicted covariance structure of class confidences with the semantic correlations encoded in pretrained text embed-dings with the geometric consistency of the class space throughout fine-tuning, resulting in more stable and interpretable confidence dis...
Ao Zhou, Zhi-Wei Jiang, Zi-Feng Cheng et al.
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