CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learning

arXiv:2404.09640v1 Announce Type: new
Abstract: Zero-shot learning (ZSL) enables the recognition of novel classes by leveraging semantic knowledge transfer from known to unknown categories. This knowledge, typically encapsulated in attribute descriptions, aids in identifying class-specific visual features, thus facilitating visual-semantic alignment and improving ZSL performance. However, real-world challenges such as distribution imbalances and attribute co-occurrence among instances often hinder the discernment of local variances in images, a problem exacerbated by the scarcity of fine-grained, region-specific attribute annotations. Moreover, the variability …

arxiv cs.cv deep learning modal through type zero-shot