DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer
About
Recently, there has been a flurry of industrial activity around logo recognition, such as Ditto's service for marketers to track their brands in user-generated images, and LogoGrab's mobile app platform for logo recognition. However, relatively little academic or open-source logo recognition progress has been made in the last four years. Meanwhile, deep convolutional neural networks (DCNNs) have revolutionized a broad range of object recognition applications. In this work, we apply DCNNs to logo recognition. We propose several DCNN architectures, with which we surpass published state-of-art accuracy on a popular logo recognition dataset.
Forrest N. Iandola, Anting Shen, Peter Gao, Kurt Keutzer• 2015
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Logo Recognition | FlickrLogos-32 (test) | -- | 13 | |
| Logo Classification | FlickrLogos-32 (test) | Accuracy89.6 | 10 | |
| Logo Detection | FlickrLogos-32 | mAP74.4 | 8 | |
| Localized Logo Detection | FlickrLogos-32 (test) | adidas61.6 | 2 | |
| Non-localized Logo Detection | FlickrLogos-32 (test) | Brand Accuracy: adidas44 | 1 |
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