WeEdit: A Dataset, Benchmark and Glyph-Guided Framework for Text-centric Image Editing
Instruction-based image editing aims to modify specific content within existing images according to user-provided instructions while preserving non-target regions. Beyond traditional object- and style-centric manipulation, text-centric image editing focuses on modifying, translating, or rearranging textual elements embedded within images. However, existing leading models often struggle to execute complex text editing precisely, frequently producing blurry or hallucinated characters. We attribute these failures primarily to the lack of specialized training paradigms tailored for text-centric editing, as well as the absence of large-scale datasets and standardized benchmarks necessary for a...
| Authors | Hui Zhang, Juntao Liu, Zongkai Liu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 March 2026 |
| Last updated at source | 17 July 2026 |
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- ysharma/Qwen-Image-2.1-image-translator-LoRAModel · cited by
- HuiZhang0812/WeEdit_benchmarkDataset · cited by
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