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HVQ-VAE: Variational auto-encoder with hyperbolic vector quantization

delete2025-05-21
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PRE
AI
S
Shangyu Chen
P
Pengfei Fang
M
Mehrtash Harandi
T
Trung Le
J
Jianfei Cai
D
Dinh Phung
DOI:10.1016/j.cviu.2025.104392delete
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Abstract

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

Computer Vision and Image Understanding cover
Computer Vision and Image Understanding
IF:
3.5
Papers:
428
Citations:
7.3K

Organization

No organization information available