Seeing is Believing: Aligning Prompt Rewriting with Visual Anchors for Text-to-Image Generation

arXiv:2606.08492v1 Announce Type: cross Abstract: Despite the impressive capabilities of text-to-image (T2I) models, an intent-generation gap often persists due to the brevity and ambiguity of user prompts. Existing approaches primarily polish the prompt for fluency and readability. However, the enhancement process still lacks visual grounding. As a result, the rewriter may over-infer missing details, causing an intent-generation gap. To address this limitation, we propose FaithRewriter, a novel prompt-enhancement framework for T2I generation. Specifically, FaithRewriter first leverages a mult
The rapid advancement of text-to-image models has exposed prompt limitations, creating a critical need for more sophisticated prompt engineering solutions that ensure user intent is accurately captured.
Improving the fidelity of text-to-image generation through more precise prompt interpretation can unlock greater creative potential and higher utility for these AI systems across various industries.
The explicit incorporation of 'visual anchors' into prompt rewriting marks a shift towards more grounded and less ambiguous AI generation, potentially reducing the 'intent-generation gap'.
- · Text-to-image model developers
- · Generative AI users
- · Digital artists and designers
- · AI content platforms
- · Manual prompt engineers (for simpler tasks)
- · AI models without robust prompt interpretation
- · Generic prompt enhancement tools
More accurate and controllable AI-generated imagery becomes widely accessible, reducing iteration cycles for creative professionals.
This improved control fosters new applications and business models where specific visual outputs are critical, such as product design or film pre-visualization.
The enhanced ability to precisely direct AI generation could lead to ethical discussions around the creation of highly convincing, yet unreal, visual content and its implications for truth and perception.
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Read at arXiv cs.AI