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.
68db6506d2bf1f4b15ec75fc
Tomoyuki Suzuki
68db6506d2bf1f4b15ec75fd
Kang-Jun Liu
68db6506d2bf1f4b15ec75fe
Naoto Inoue
68db6506d2bf1f4b15ec75ff
Kota Yamaguchi
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.
LayerD decomposes raster images into editable layers using iterative extraction and refinement, outperforming existing methods and enabling use with advanced image generators.
layer representation raster image decomposition foreground layers uniform appearance quality metric state-of-the-art image generators layer-based editing