Flux-Sculptor: Text-Driven Rich-Attribute Portrait Editing through Decomposed Spatial Flow Control

• URL: http://arxiv.org/abs/2507.03979v1
• Date: Sat, 05 Jul 2025 10:08:39 GMT
• Title: Flux-Sculptor: Text-Driven Rich-Attribute Portrait Editing through Decomposed Spatial Flow Control
• Authors: Tianyao He, Runqi Wang, Yang Chen, Dejia Song, Nemo Chen, Xu Tang, Yao Hu,
• Abstract summary: Flux-Sculptor is a flux-based framework designed for precise text-driven portrait editing.<n>Our framework introduces a Prompt-Aligned Spatial Locator (PASL) to accurately identify relevant editing regions.<n>Experiments demonstrate that Flux-Sculptor surpasses existing methods in rich-attribute editing and facial information preservation.
• Score: 24.057959328107387
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Text-driven portrait editing holds significant potential for various applications but also presents considerable challenges. An ideal text-driven portrait editing approach should achieve precise localization and appropriate content modification, yet existing methods struggle to balance reconstruction fidelity and editing flexibility. To address this issue, we propose Flux-Sculptor, a flux-based framework designed for precise text-driven portrait editing. Our framework introduces a Prompt-Aligned Spatial Locator (PASL) to accurately identify relevant editing regions and a Structure-to-Detail Edit Control (S2D-EC) strategy to spatially guide the denoising process through sequential mask-guided fusion of latent representations and attention values. Extensive experiments demonstrate that Flux-Sculptor surpasses existing methods in rich-attribute editing and facial information preservation, making it a strong candidate for practical portrait editing applications. Project page is available at https://flux-sculptor.github.io/.

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