Papers by Hongxi Wei

1 papers
GL-GAN: Perceiving and Integrating Global and Local Styles for Handwritten Text Generation with Mamba (2025.coling-main)

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Challenge: Existing models lack the ability to perceive and integrate handwriting styles, which affects the realism of the synthesized samples.
Approach: They propose a Hybrid Style Encoder that captures global and local styles and integrates them into a Dynamic Feature Enhancement Module (DFEM).
Outcome: The proposed model outperforms state-of-the-art models on two widely used handwriting datasets and can provide training data for handwritten text recognition and signature verification.

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