From Fragment to One Piece: A Survey on AI-Driven Graphic Design
- URL: http://arxiv.org/abs/2503.18641v1
- Date: Mon, 24 Mar 2025 13:05:09 GMT
- Title: From Fragment to One Piece: A Survey on AI-Driven Graphic Design
- Authors: Xingxing Zou, Wen Zhang, Nanxuan Zhao,
- Abstract summary: The survey covers various subtasks, including visual element perception and generation, aesthetic and semantic understanding, layout analysis, and generation.<n>Despite significant progress, challenges remain to understanding human intent, ensuring interpretability, and maintaining control over multilayered compositions.
- Score: 19.042522345775193
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This survey provides a comprehensive overview of the advancements in Artificial Intelligence in Graphic Design (AIGD), focusing on integrating AI techniques to support design interpretation and enhance the creative process. We categorize the field into two primary directions: perception tasks, which involve understanding and analyzing design elements, and generation tasks, which focus on creating new design elements and layouts. The survey covers various subtasks, including visual element perception and generation, aesthetic and semantic understanding, layout analysis, and generation. We highlight the role of large language models and multimodal approaches in bridging the gap between localized visual features and global design intent. Despite significant progress, challenges remain to understanding human intent, ensuring interpretability, and maintaining control over multilayered compositions. This survey serves as a guide for researchers, providing information on the current state of AIGD and potential future directions\footnote{https://github.com/zhangtianer521/excellent\_Intelligent\_graphic\_design}.
Related papers
- Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook [85.43403500874889]
Retrieval-augmented generation (RAG) has emerged as a pivotal technique in artificial intelligence (AI)
Recent advancements in RAG for embodied AI, with a particular focus on applications in planning, task execution, multimodal perception, interaction, and specialized domains.
arXiv Detail & Related papers (2025-03-23T10:33:28Z) - Data Analysis in the Era of Generative AI [56.44807642944589]
This paper explores the potential of AI-powered tools to reshape data analysis, focusing on design considerations and challenges.
We explore how the emergence of large language and multimodal models offers new opportunities to enhance various stages of data analysis workflow.
We then examine human-centered design principles that facilitate intuitive interactions, build user trust, and streamline the AI-assisted analysis workflow across multiple apps.
arXiv Detail & Related papers (2024-09-27T06:31:03Z) - Diffusion-Based Visual Art Creation: A Survey and New Perspectives [51.522935314070416]
This survey explores the emerging realm of diffusion-based visual art creation, examining its development from both artistic and technical perspectives.
Our findings reveal how artistic requirements are transformed into technical challenges and highlight the design and application of diffusion-based methods within visual art creation.
We aim to shed light on the mechanisms through which AI systems emulate and possibly, enhance human capacities in artistic perception and creativity.
arXiv Detail & Related papers (2024-08-22T04:49:50Z) - Inspired by AI? A Novel Generative AI System To Assist Conceptual Automotive Design [6.001793288867721]
Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process.
Many practice designers use text-based searches on platforms like Pinterest to gather image ideas, followed by sketching on paper or using digital tools to develop concepts.
Emerging generative AI techniques, such as diffusion models, offer a promising avenue to streamline these processes by swiftly generating design concepts based on text and image inspiration inputs.
arXiv Detail & Related papers (2024-06-06T17:04:14Z) - Indexing Analytics to Instances: How Integrating a Dashboard can Support Design Education [14.45375751032367]
We develop a research artifact integrating a design analytics dashboard with design instances, and the design environment that students use to create them.
We develop research implications addressing how AI-based design analytics can support instructors' assessment and feedback experiences in situated course contexts.
arXiv Detail & Related papers (2024-04-08T11:33:58Z) - From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models [98.41645229835493]
Data visualization in the form of charts plays a pivotal role in data analysis, offering critical insights and aiding in informed decision-making.<n>Large foundation models, such as large language models, have revolutionized various natural language processing tasks.<n>This survey paper serves as a comprehensive resource for researchers and practitioners in the fields of natural language processing, computer vision, and data analysis.
arXiv Detail & Related papers (2024-03-18T17:57:09Z) - The role of interface design on prompt-mediated creativity in Generative
AI [0.0]
We analyze more than 145,000 prompts from two Generative AI platforms.
We find that users exhibit a tendency towards exploration of new topics over exploitation of concepts visited previously.
arXiv Detail & Related papers (2023-11-30T22:33:34Z) - InstructDiffusion: A Generalist Modeling Interface for Vision Tasks [52.981128371910266]
We present InstructDiffusion, a framework for aligning computer vision tasks with human instructions.
InstructDiffusion could handle a variety of vision tasks, including understanding tasks and generative tasks.
It even exhibits the ability to handle unseen tasks and outperforms prior methods on novel datasets.
arXiv Detail & Related papers (2023-09-07T17:56:57Z) - Visual Firewall Log Analysis -- At the Border Between Analytical and
Appealing [1.8692254863855962]
We present our design study on developing an interactive visual firewall log analysis system in collaboration with an IT service provider.
We describe the human-centered design process, in which we additionally considered hedonic qualities.
As a reflection, we propose the extension of a widely used design study process with a track for an additional focus on hedonic qualities.
arXiv Detail & Related papers (2022-09-08T10:39:04Z) - SGEITL: Scene Graph Enhanced Image-Text Learning for Visual Commonsense
Reasoning [61.57887011165744]
multimodal Transformers have made great progress in the task of Visual Commonsense Reasoning.
We propose a Scene Graph Enhanced Image-Text Learning framework to incorporate visual scene graphs in commonsense reasoning.
arXiv Detail & Related papers (2021-12-16T03:16:30Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.