Summary of Design-o-meter: Towards Evaluating and Refining Graphic Designs, by Sahil Goyal et al.
Design-o-meter: Towards Evaluating and Refining Graphic Designs
by Sahil Goyal, Abhinav Mahajan, Swasti Mishra, Prateksha Udhayanan, Tripti Shukla, K J Joseph, Balaji Vasan Srinivasan
First submitted to arxiv on: 22 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In a breakthrough that combines art and AI, researchers have developed Design-o-meter, a data-driven approach to evaluate and refine graphic designs. This innovative methodology can quantify the quality of designs and suggest modifications to improve their visual appeal. By harnessing machine learning techniques, designers can accelerate content production while ensuring high-quality outputs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Graphic design is an essential form of communication that has become even more crucial with the rise of digital media. A team of researchers has created Design-o-meter, a unique system that evaluates and improves graphic designs using data-driven methods. This approach can analyze the quality of various designs and provide suggestions for modifications to enhance their visual appeal. |
Keywords
» Artificial intelligence » Machine learning
