A deep hashing method that replaces one-hot class labels with semantic hierarchy distances and adds an empirical KL loss, improving binary-code hierarchical retrieval on CIFAR-100 and ImageNet.
Mean Local Group Average Precision (mLGAP): A New Performance Metric for Hashing-based Retrieval
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SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
A deep hashing method that replaces one-hot class labels with semantic hierarchy distances and adds an empirical KL loss, improving binary-code hierarchical retrieval on CIFAR-100 and ImageNet.