GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization

GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization

This paper introduces GA-VAE, a fine-tuning framework that enhances local feature representation in pre-trained Vector Quantized-VAE (VQ-VAE) models through genetic algorithm-based optimization. While VQ-VAE models have shown promise in learning discrete latent representations for complex data distr...

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Bibliographic Details
Main Authors: Jinghui Jiang, Dongjoon Kim, Bohyoung Kim, Yeong-Gil Shin
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
VQ-VAE
genetic algorithm
local feature learning
token optimization
fine-tuning
Online Access:https://ieeexplore.ieee.org/document/10890968/
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https://ieeexplore.ieee.org/document/10890968/

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