Famous Companies Use More Letters in Logo:A Large-Scale Analysis of Text Area in Logo
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Abstract (arXiv)
This paper analyzes a large number of logo images from the LLD-logo dataset, by recent deep learning-based techniques, to understand not only design trends of logo images and but also the correlation to their owner company. Especially, we focus on three correlations between logo images and their text areas, between the text areas and the number of followers on Twitter, and between the logo images and the number of followers. Various findings include the weak positive correlation between the text area ratio and the number of followers of the company. In addition, deep regression and deep ranking methods can catch correlations between the logo images and the number of followers.
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References · 8
- 2019Character Region Awareness for Text Detectioncited by 273
- 2020Unsupervised Domain Adaptation via Structurally Regularized Deep Clusteringcited by 140
- 2020Online Deep Clustering for Unsupervised Representation Learningcited by 99
- 2019A Deep Look into Neural Ranking Models for Information Retrievalcited by 79
- 2018Clustering with Deep Learning: Taxonomy and New Methodscited by 45
- 2019Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classificationcited by 22
- 2017Logo Synthesis and Manipulation with Clustered Generative Adversarial Networkscited by 20
- 2018An Universal Image Attractiveness Ranking Frameworkcited by 1
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