mlsanityData to 14 Oct 2026

Infographics Wizard: Flexible Infographics Authoring and Design Exploration

arXiv 2204.09904 ↗First posted 21 Apr 2022cs.HC cs.AI cs.CVcited by 3

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Abstract (arXiv)

Infographics are an aesthetic visual representation of information following specific design principles of human perception. Designing infographics can be a tedious process for non-experts and time-consuming, even for professional designers. With the help of designers, we propose a semi-automated infographic framework for general structured and flow-based infographic design generation. For novice designers, our framework automatically creates and ranks infographic designs for a user-provided text with no requirement for design input. However, expert designers can still provide custom design inputs to customize the infographics. We will also contribute an individual visual group (VG) designs dataset (in SVG), along with a 1k complete infographic image dataset with segmented VGs in this work. Evaluation results confirm that by using our framework, designers from all expertise levels can generate generic infographic designs faster than existing methods while maintaining the same quality as hand-designed infographics templates.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 12 of its 46 references that are in the map. First posted on arXiv 21 Apr 2022.

Builds on

12 of 46 references.

References · 12

  1. 2017Mask R-CNNcited by 7,277
  2. 2018Data2Vis: Automatic Generation of Data Visualizations Using Sequence to Sequence Recurrent Neural Networkscited by 48
  3. 2018VizML: A Machine Learning Approach to Visualization Recommendationcited by 38
  4. 2019Text-to-Viz: Automatic Generation of Infographics from Proportion-Related Natural Language Statementscited by 31
  5. 2020Predicting Visual Importance Across Graphic Design Typescited by 30
  6. 2019Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timelinecited by 20
  7. 2021InfoColorizer: Interactive Recommendation of Color Palettes for Infographicscited by 15
  8. 2018Synthetically Trained Icon Proposals for Parsing and Summarizing Infographicscited by 6
  9. 2019Task Classification Model for Visual Fixation, Exploration, and Searchcited by 5
  10. 2017Understanding Infographics through Textual and Visual Tag Predictioncited by 4
  11. 2019ICE: An Interactive Configuration Explorer for High Dimensional Categorical Parameter Spacescited by 2
  12. 2021User-Centric Semi-Automated Infographics Authoring and Recommendationcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 2.

3 papers.