Papers › Large-Scale Visual Font Recognition
Large-Scale Visual Font Recognition
Guang Chen, Jianchao Yang, Hailin Jin, Jonathan Brandt, Eli Shechtman, Aseem Agarwala, Tony X. Han
This paper addresses the large-scale visual font recognition (VFR) problem, which aims at automatic identification of the typeface, weight, and slope of the text in an image or photo without any knowledge of content. Although visual font recognition has many practical applications, it has largely been neglected by the vision community. To address the VFR problem, we construct a large-scale dataset containing 2,420 font classes, which easily exceeds the scale of most image categorization datasets in computer vision. As font recognition is inherently dynamic and open-ended, i.e., new classes and data for existing categories are constantly added to the database over time, we propose a scalable solution based on the nearest class mean classifier (NCM). The core algorithm is built on local feature embedding, local feature metric learning and max-margin template selection, which is naturally amenable to NCM and thus to such open-ended classification problems. The new algorithm can generalize to new classes and new data at little added cost. Extensive experiments demonstrate that our approach is very effective on our synthetic test images, and achieves promising results on real world test images.
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Tasks
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Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Font Recognition | VFR-2420 | LFE (FS, template model size 2048) | Top 1 Accuracy | 72.5 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-2420 | LFE (FS, template model size 2048) | Top 10 Accuracy | 96.87 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-2420 | LFE (FS, template model size 2048) | Top 5 Accuracy | 93.45 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-447 | LFE (FS, template model size 2048) | Top 1 Accuracy | 91.35 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-447 | LFE (FS, template model size 2048) | Top 10 Accuracy | 99.62 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-447 | LFE (FS, template model size 2048) | Top 5 Accuracy | 98.80 | #1 of 1 | Archive leaderboard | report |
| Font Recognition | VFR-Wild | LFE (FS, template model size 2048) | Top 1 Accuracy | 52.61 | #2 of 2 | Archive leaderboard | report |
| Font Recognition | VFR-Wild | LFE (FS, template model size 2048) | Top 10 Accuracy | 62.14 | #2 of 2 | Archive leaderboard | report |
| Font Recognition | VFR-Wild | LFE (FS, template model size 2048) | Top 5 Accuracy | 58.4 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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