PSA-HWT: handwritten font generation based on pyramid squeeze attention.

ABSTRACT: The generator, which combines convolutional neural network (CNN) and Transformer as its core modules, serves as the primary model for the handwriting font generation network and demonstrates effective performance. However, there are still problems with insufficient feature extraction in the overall structure of the font, the thickness of strokes, and the curvature of strokes, resulting in subpar detail in the generated fonts. To solve the problems, we propose a method for constructing a handwritten font generation model based on Pyramid Squeeze Attention, called PSA-HWT. The PSA-HWT model is divided into two parts: an encoder and a decoder. In the encoder, a multi-branch structure is used to extract spatial information at different scales from the input feature map, achieving multi-scale f

SUBMITTER: Zhao H 

PROVIDER: S-EPMC11639151 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature