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HVQ-VAE: Variational auto-encoder with hyperbolic vector quantization
DOI:10.1016/j.cviu.2025.104392.png)
Abstract
En 中文
• This paper introduces HVQ-VAE enhancing traditional VQ-VAE with geometric priors. • The encoder of HVQ-VAE can learn the inherent hierarchical structures from the data. • Demonstrates superior image reconstruction and learning efficiency. • HVQ-VAE’s geometric prior leads to higher codebook usage, faster convergence, and improved performance. • HVQ-VAE employs Riemannian optimization to update the codebook within hyperbolic space.
Journal
IF:
3.5
Papers:
428
Citations:
7.3K
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