Font Generation with Deep Learning

Module: Generative AI | Difficulty: Advanced

Few-Shot Font Generation

Glyph Decomposition

Style Transfer

class FewShotFont(nn.Module):
    def __init__(self, content_encoder, style_encoder, decoder):
        super().__init__()
        self.content = content_encoder
        self.style = style_encoder
        self.decoder = decoder
    def forward(self, char_img, style_imgs):
        c = self.content(char_img)
        s = self.style(torch.cat(style_imgs, dim=0))
        return self.decoder(c, s)

| Shots | FID | LPIPS | SSIM | |-------|-----|-------|------| | 1 | 45.2 | 0.28 | 0.62 | | 3 | 28.7 | 0.18 | 0.75 | | 5 | 21.3 | 0.14 | 0.82 | | 10 | 15.8 | 0.11 | 0.88 |

Research Insight: Font generation benefits from disentangling content (character identity) and style (typographic features). Self-supervised pre-training on large font datasets improves few-shot performance by 30%.