arXiv:2606. 13382v1 Announce Type: cross Abstract: Few-shot font generation simultaneously requires global structural completeness and fine-grained local style fidelity.
Few-shot font generation simultaneously requires global structural completeness and fine-grained local style fidelity. Existing methods usually either rely on global content-style modeling, which is robust but imperfectly disentangled, or emphasize component/local modeling, which captures fine details but relies heavily on local priors and reference coverage.
LoGAN is a VLM-based agentic framework designed for few-shot multilingual font localization. It takes a handful of glyphs or logo letters and generates complete character sets across many languages, including CJK, by combining a glyph-level diffusion model, style finetuning, spacing/kerning transfer, and texture expansion. The method outperforms specialized font generators and state‑of‑the‑art image editors in glyph fidelity, style, texture, and kerning consistency on datasets covering more than 27 languages.
arXiv:2507. 17853v2 Announce Type: replace-cross Abstract: Recent advances in text-to-image (T2I) generation have led to impressive visual results.
GlyphAnchor is a new method that improves visual text rendering in image generation and editing models by adding lightweight glyph patch conditions anchored to the target image’s positional encoding. The approach is trained with staged supervised finetuning and text-aware post‑training, and it works with both text‑to‑image and image‑editing diffusion transformers. Experiments on various backbones and the newly introduced InfoTextBench benchmark show that GlyphAnchor consistently enhances text fidelity while maintaining overall image quality, especially for long, complex, or densely arranged text and rare characters.
arXiv:2609.38636v1 Announce Type: new Abstract: We introduce Scene Text Editing with Preserved Style (STEPS), a novel diffusion model architecture for quality text replacement in images. Scene Text E...
arXiv:2606. 05261v1 Announce Type: cross Abstract: Variable fonts enable continuous variation of glyph geometry along semantic design axes such as weight, width, slant, and optical size.
arXiv:2609.22916v1 Announce Type: new Abstract: Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit la...
arXiv:2608. 19637v1 Announce Type: new Abstract: Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition.
Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition. Despite recent progress in instruction-based image editing, general-purpose models remain unreliable in this setting: they often omit or incorrectly render the target text, place it over salient products or pre-existing content, and produce structurally distorted or visually inconsistent glyphs.
arXiv:2607. 00374v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification.
Artistic image synthesis aims to recreate the expressive visual identity of a target artist, yet existing methods often fail to capture an artist's global style. Conventional style transfer methods transfer the style of one or a few reference artworks to a content image in a One-to-One manner, making them effective for artwork-level stylization but limited in representing the broader stylistic distribution of an artist.
arXiv:2609.08032v1 Announce Type: cross Abstract: We introduce FlexMoGen, a novel framework for flexible human motion synthesis conditioned on both natural language descriptions and motion style refe...