SOTAVerified

Font Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 52 papers

TitleStatusHype
DGFont++: Robust Deformable Generative Networks for Unsupervised Font GenerationCode2
FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive LearningCode2
Few-shot Compositional Font Generation with Dual MemoryCode1
GAS-NeXt: Few-Shot Cross-Lingual Font GeneratorCode1
Generate Like Experts: Multi-Stage Font Generation by Incorporating Font Transfer Process into Diffusion ModelsCode1
VQ-Font: Few-Shot Font Generation with Structure-Aware Enhancement and QuantizationCode1
StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke EncodingCode1
Few-Shot Font Generation by Learning Fine-Grained Local StylesCode1
Instance Segmentation for Chinese Character Stroke Extraction, Datasets and BenchmarksCode1
DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality LearningCode1
Few shot font generation via transferring similarity guided global style and quantization local styleCode1
Neural Transformation Fields for Arbitrary-Styled Font GenerationCode1
CF-Font: Content Fusion for Few-shot Font GenerationCode1
Look Closer to Supervise Better: One-Shot Font Generation via Component-Based DiscriminatorCode1
Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized ExpertsCode1
MX-Font++: Mixture of Heterogeneous Aggregation Experts for Few-shot Font GenerationCode1
Few-shot Font Generation with Localized Style Representations and FactorizationCode1
Few-shot Font Generation with Weakly Supervised Localized RepresentationsCode1
DG-Font: Deformable Generative Networks for Unsupervised Font GenerationCode1
Font Style that Fits an Image -- Font Generation Based on Image ContextCode1
Diff-Font: Diffusion Model for Robust One-Shot Font GenerationCode1
DeepCalliFont: Few-shot Chinese Calligraphy Font Synthesis by Integrating Dual-modality Generative ModelsCode1
ZiGAN: Fine-grained Chinese Calligraphy Font Generation via a Few-shot Style Transfer Approach—0
Automatic Generation of Chinese Handwriting via Fonts Style Representation Learning—0
Automatic Generation of Typographic Font from a Small Font Subset—0
Design and Development of a Framework For Stroke-Based Handwritten Gujarati Font Generation—0
Efficient and Scalable Chinese Vector Font Generation via Component Composition—0
Few-shot Font Generation by Learning Style Difference and Similarity—0
Few-Shot Font Generation with Deep Metric Learning—0
Font-Agent: Enhancing Font Understanding with Large Language Models—0
Font Generation with Missing Impression Labels—0
FontNet: Closing the gap to font designer performance in font synthesis—0
FontTransformer: Few-shot High-resolution Chinese Glyph Image Synthesis via Stacked Transformers—0
GANet: Glyph-Attention Network for Few-Shot Font Generation—0
Handwritten Chinese Font Generation with Collaborative Stroke Refinement—0
Joint Implicit Neural Representation for High-fidelity and Compact Vector Fonts—0
Learning Perceptual Manifold of Fonts—0
Local Style Awareness of Font Images—0
Neural Style Difference Transfer and Its Application to Font Generation—0
VecFusion: Vector Font Generation with Diffusion—0
XMP-Font: Self-Supervised Cross-Modality Pre-training for Few-Shot Font Generation—0
AdaptiFont: Increasing Individuals' Reading Speed with a Generative Font Model and Bayesian Optimization—0
One-Shot Multilingual Font Generation Via ViT—0
Pyramid Embedded Generative Adversarial Network for Automated Font Generation—0
SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation—0
SGCE-Font: Skeleton Guided Channel Expansion for Chinese Font Generation—0
Skeleton and Font Generation Network for Zero-shot Chinese Character Generation—0
StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding—0
SVG Vector Font Generation for Chinese Characters with Transformer—0
Learning Typographic StyleCode0
Show:102550
← PrevPage 1 of 2Next →

No leaderboard results yet.