LayerD: Decomposing Raster Graphic Designs into Layers

Designers craft and edit graphic designs in a layer representation, but layer-based editing becomes impossible once composited into a raster image. In this work, we propose LayerD, a method to decompose raster graphic designs into layers for re-editable creative workflow. LayerD addresses the decomposition task by iteratively extracting unoccluded foreground layers. We propose a simple yet effective refinement approach taking advantage of the assumption that layers often exhibit uniform appearance in graphic designs. As decomposition is ill-posed and the ground-truth layer structure may not be reliable, we develop a quality metric that addresses the difficulty. In experiments, we show that LayerD successfully achieves high-quality decomposition and outperforms baselines. We also demonstrate the use of LayerD with state-of-the-art image generators and layer-based editing.

Publication Details

Journal
ArXiv.org
Published
2025-09-29
Primary Topic
Oceanographic and Atmospheric Processes
Type
article
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article

LayerD: Decomposing Raster Graphic Designs into Layers

ArXiv.org
Oceanographic and Atmospheric Processes
article

LayerD: Decomposing Raster Graphic Designs into Layers

article en

Abstract

Designers craft and edit graphic designs in a layer representation, but layer-based editing becomes impossible once composited into a raster image. In this work, we propose LayerD, a method to decompose raster graphic designs into layers for re-editable creative workflow. LayerD addresses the decomposition task by iteratively extracting unoccluded foreground layers. We propose a simple yet effective refinement approach taking advantage of the assumption that layers often exhibit uniform appearance in graphic designs. As decomposition is ill-posed and the ground-truth layer structure may not be reliable, we develop a quality metric that addresses the difficulty. In experiments, we show that LayerD successfully achieves high-quality decomposition and outperforms baselines. We also demonstrate the use of LayerD with state-of-the-art image generators and layer-based editing.

ArXiv.org
Openalex Percentile: Top 42%
Oceanographic and Atmospheric Processes
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LayerD: Decomposing Raster Graphic Designs into Layers · ArXiv.org (2025) | TGRS Research Map | TGRS