Structure-Preserving Zero-Shot Image Editing via Stage-Wise Latent Injection in Diffusion Models

• URL: http://arxiv.org/abs/2504.15723v1
• Date: Tue, 22 Apr 2025 09:18:16 GMT
• Title: Structure-Preserving Zero-Shot Image Editing via Stage-Wise Latent Injection in Diffusion Models
• Authors: Dasol Jeong, Donggoo Kang, Jiwon Park, Hyebean Lee, Joonki Paik,
• Abstract summary: We propose a diffusion-based framework for zero-shot image editing that unifies text-guided and reference-guided approaches without requiring fine-tuning.<n>Our method leverages diffusion inversion and timestep-specific null-text embeddings to preserve the structural integrity of the source image.<n>Cross-attention with reference latents facilitates semantic alignment between the source and reference.
• Score: 3.3845637570565814
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a diffusion-based framework for zero-shot image editing that unifies text-guided and reference-guided approaches without requiring fine-tuning. Our method leverages diffusion inversion and timestep-specific null-text embeddings to preserve the structural integrity of the source image. By introducing a stage-wise latent injection strategy-shape injection in early steps and attribute injection in later steps-we enable precise, fine-grained modifications while maintaining global consistency. Cross-attention with reference latents facilitates semantic alignment between the source and reference. Extensive experiments across expression transfer, texture transformation, and style infusion demonstrate state-of-the-art performance, confirming the method's scalability and adaptability to diverse image editing scenarios.

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