Efficient Scene-Text Refinement via Pixel-Space Grouped Image Generation
Generated images often have coherent layouts and visual content, yet local errors in small text and complex characters still limit their readability and practical use. Scene-text refinement requires accuracy, preservation, and efficiency. Existing methods based on variational autoencoders (VAEs) can lose fine strokes during reconstruction, while full-image editing can shift background colors. In this work, we introduce PixText, a model that formulates local text refinement as grouped image generation in pixel space. Conditioned on the original image, PixText generates only the target regions, preserves unedited content, and uses MeanFlow for four-step generation. We further introduce Text...
| Authors | Yaoli Liu, Guo-Hua Wang, Yiyang Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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