TextMaster: A Unified Framework for Realistic Text Editing via Glyph-Style Dual-Control
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866912940587745280 |
|---|---|
| author | Yan, Zhenyu Wang, Jian Wang, Aoqiang Li, Yuhan Shang, Wenxiang Lin, Ran |
| author_facet | Yan, Zhenyu Wang, Jian Wang, Aoqiang Li, Yuhan Shang, Wenxiang Lin, Ran |
| contents | In image editing tasks, high-quality text editing capabilities can significantly reduce both human and material resource costs. Existing methods, however, face significant limitations in terms of stroke accuracy for complex text and controllability of generated text styles. To address these challenges, we propose TextMaster, a solution capable of accurately editing text across various scenarios and image regions, while ensuring proper layout and controllable text style. Our method enhances the accuracy and fidelity of text rendering by incorporating high-resolution standard glyph information and applying perceptual loss within the text editing region. Additionally, we leverage an attention mechanism to compute intermediate layer bounding box regression loss for each character, enabling the model to learn text layout across varying contexts. Furthermore, we propose a novel style injection technique that enables controllable style transfer for the injected text. Through comprehensive experiments, we demonstrate the state-of-the-art performance of our method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_09879 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TextMaster: A Unified Framework for Realistic Text Editing via Glyph-Style Dual-Control Yan, Zhenyu Wang, Jian Wang, Aoqiang Li, Yuhan Shang, Wenxiang Lin, Ran Computer Vision and Pattern Recognition In image editing tasks, high-quality text editing capabilities can significantly reduce both human and material resource costs. Existing methods, however, face significant limitations in terms of stroke accuracy for complex text and controllability of generated text styles. To address these challenges, we propose TextMaster, a solution capable of accurately editing text across various scenarios and image regions, while ensuring proper layout and controllable text style. Our method enhances the accuracy and fidelity of text rendering by incorporating high-resolution standard glyph information and applying perceptual loss within the text editing region. Additionally, we leverage an attention mechanism to compute intermediate layer bounding box regression loss for each character, enabling the model to learn text layout across varying contexts. Furthermore, we propose a novel style injection technique that enables controllable style transfer for the injected text. Through comprehensive experiments, we demonstrate the state-of-the-art performance of our method. |
| title | TextMaster: A Unified Framework for Realistic Text Editing via Glyph-Style Dual-Control |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2410.09879 |