"Authors of Multi-Similarity loss paper used only hard negatives and positives for training and discarded all other pairs as they contribute little to no improvement and sometimes degraded the performance as well. Choosing only those pairs that carries the most information also make the algo "
"Authors of Multi-Similarity loss paper used only hard negatives and positives for training and discarded all other pairs as they contribute little to no improvement and sometimes degraded the performance as well. Choosing only those pairs that carries the most information also make the algo "
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Multi-Similarity Loss for Deep Metric Learning
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