Layer3D: A 3D Layered Representation for Multiview Vector Graphics
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Date
2026
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
We present Layer3D, a novel 3D neural representation that models objects as collections of decomposable neural implicit primitives. These primitives enable the generation of layered images with consistent correspondences across viewpoints, establishing a flexible framework for multiview vector graphics decomposition. Integrated into a text-to-3D pipeline via Score Distillation Sampling (SDS), Layer3D learns to generate primitives with diverse shape topologies while preserving structural coherence. To ensure front-to-back ordering required for 2D flat graphics, our method incorporates front-to-back rendering and shape regularization constraints. Experimental results demonstrate that Layer3D consistently produces meaningful, topology-diverse layers across multiple views, thereby facilitating intuitive and effective layer-based vector editing.
Description
@article{10.1111:cgf.70375,
journal = {Computer Graphics Forum},
title = {{Layer3D: A 3D Layered Representation for Multiview Vector Graphics}},
author = {Guan, Zhongyue and Hu, Yixin and Wang, Zeyu},
year = {2026},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70375}
}