InkIdeator: Supporting Chinese-Style Visual Design Ideation via AI-Infused Exploration of Chinese Paintings

2026-01-26

AI Summary

This study addresses the challenge visual designers face in efficiently extracting and integrating multidimensional cultural elements—such as symbols, emotions, composition, and stylistic features—from traditional Chinese painting when creating works in a Chinese aesthetic. To this end, the paper presents the first structured representation of cultural dimensions inherent in Chinese painting and introduces a culture-aware generative design system built upon multimodal large language models. The system supports theme-linked symbol recommendation, interpretation of dimension-specific keywords, and generation of visual exemplars conditioned on fused cultural keywords. User studies demonstrate that the system significantly enhances designers’ efficiency in exploring Chinese painting’s cultural elements and boosts their creative expression, with validation from professional painters. This work establishes a new paradigm for culturally intelligent AI-powered design tools.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Computer Vision: Visual Reasoning & Symbolic Representations

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions

Abstract

Visual designers often seek inspiration from Chinese paintings when tasked with creating Chinese-style illustrations, posters, etc. Our formative study (N=10) reveals that during ideation, designers learn the cultural symbols, emotions, compositions, and styles in Chinese paintings but face challenges in searching, analyzing, and integrating these dimensions. This paper leverages multi-modal large models to annotate the value of each dimension in 16,315 Chinese paintings, built on which we propose InkIdeator, an ideation support system for Chinese-style visual designs. InkIdeator suggests cultural symbols associated with the task theme, provides dimensional keywords to help analyze Chinese paintings, and generates visual examples integrating user-selected keywords. Our within-subjects study (N=12) using a baseline system without extracted dimensional keywords, along with two extended use cases by Chinese painters, indicates InkIdeator's effectiveness in creative ideation support, helping users efficiently explore cultural dimensions in Chinese paintings and visualize their ideas. We discuss implications for supporting culture-related visual design ideation with generative AI.

Problem

• Chinese-style visual design
• design ideation
• Chinese paintings
• cultural dimensions
• creative inspiration

Innovation

• multi-modal large models
• Chinese-style visual design
• cultural symbol annotation
• design ideation support
• generative AI