🔥 ReDesign: Recovering Editable Design Structures from Images via Agentic Decomposition

💡 The paper ReDesign presents a novel approach to recovering editable design structures from images, a common and costly bottleneck in modern design workflows. The problem is challenging because it requires recovering multiple attributes such as typography, vector geometry, colors, grouping, and layer ordering. The proposed method, ReDesign, uses an agentic framework that grows an editable layer hierarchy by selecting and composing specialized tools across modalities. To ensure reliability despite imperfect tool outputs, the framework introduces a verification mechanism at each expansion step, providing local accept, prune, or retry feedback that prevents error accumulation and avoids large-scale reruns.

The authors evaluate the method's editability at scale using the Figma Edit Replay Benchmark, consisting of 909 raw Figma files and 14796 controlled edit instructions that replay edits on reconstructed outputs. The results show that ReDesign achieves strong visual fidelity while delivering the highest editability across layout, color, and text edits, outperforming layered decomposition baselines and serial tool use pipelines. The paper's contributions include the introduction of the ReDesign framework, the Figma Edit Replay Benchmark, and the demonstration of the method's effectiveness in recovering editable design structures from images. Overall, the paper presents a significant advancement in the field of design recovery and editing, with potential applications in various design workflows.

📅 Published on Jul 28

🔗 Links:
• GitHub: https://github.com/huggingface
• arXiv: https://arxiv.org/abs/2607.25565
• PDF: https://arxiv.org/pdf/2607.25565
• Project Page: https://jintae-00.github.io/ReDesign/

📊 Datasets citing this paper:
• https://huggingface.co/datasets/Jintae-Park/ReDesign-Figma909

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📢 By: https://xn--r1a.website/PaperNexus

#ComputerVision #GraphicDesignAutomation #ImageProcessing #VectorGraphicsRecovery #DesignStructureExtraction