English

LICA: Layered Image Composition Annotations for Graphic Design Research

Computer Vision and Pattern Recognition 2026-03-20 v2 Artificial Intelligence

Abstract

We introduce LICA (Layered Image Composition Annotations), a large scale dataset of 1,550,244 multi-layer graphic design compositions designed to advance structured understanding and generation of graphic layouts. In addition to rendered PNG images, LICA represents each design as a hierarchical composition of typed components including text, image, vector, and group elements, each paired with rich per-element metadata such as spatial geometry, typographic attributes, opacity, and visibility. The dataset spans 20 design categories and 971,850 unique templates, providing broad coverage of real-world design structures. We further introduce graphic design video as a new and largely unexplored challenge for current vision-language models through 27,261 animated layouts annotated with per-component keyframes and motion parameters. Beyond scale, LICA establishes a new paradigm of research tasks for graphic design, enabling structured investigations into problems such as layer-aware inpainting, structured layout generation, controlled design editing, and temporally-aware generative modeling. By representing design as a system of compositional layers and relationships, the dataset supports research on models that operate directly on design structure rather than pixels alone.

Keywords

Cite

@article{arxiv.2603.16098,
  title  = {LICA: Layered Image Composition Annotations for Graphic Design Research},
  author = {Elad Hirsch and Shubham Yadav and Mohit Garg and Purvanshi Mehta},
  journal= {arXiv preprint arXiv:2603.16098},
  year   = {2026}
}
R2 v1 2026-07-01T11:23:32.602Z