Spread-Out Regularization

Proposes a regularization term that encourages embeddings (local feature descriptors) to spread out evenly across the entire space. When combined with existing distance/triplet losses, it increases representation diversity and discriminative power

Learning Spread-Out Local Feature Descriptors

Learning Spread-out Local Feature Descriptors

We propose a simple, yet powerful regularization technique that can be used to significantly improve both the pairwise and triplet losses in learning local feature descriptors. The idea is that in...

https://arxiv.org/abs/1708.06320

Spread-Out Regularization

Learning Spread-Out Local Feature Descriptors

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