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About Von Mises-Fisher Mixture Model-Based Deep Learning: Application To Face Verification
1. The document proposes a von Mises-Fisher mixture model (vMFMM) for deep learning of directional features like those used in face verification. vMFMM models deep features as a mixture of von Mises-Fisher distributions. 2. A novel von Mises-Fisher mixture loss (vMFML) is derived from the vMFMM that enables discriminative learning by compacting intra-class features while repulsing inter-class features. 3. Extensive experiments on 4 face datasets show the proposed vMFML achieves state-of-the-art or competitive results, demonstrating the effectiveness and generalization ability of the approach for face verification.
Detailed Information
| Author: | ['assasaa asasa '] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 16 |
| Language: | English |
| Format: | |
| Price: | FREE |
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