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Papers/DeepLogo: Hitting Logo Recognition with the Deep Neural Ne...

DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer

Forrest N. Iandola, Anting Shen, Peter Gao, Kurt Keutzer

2015-10-07Logo RecognitionImage ClassificationObject Recognition2D Object DetectionObject Detection
PaperPDF

Abstract

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.

Results

TaskDatasetMetricValueModel
Object DetectionFlickrLogos-32MAP74.4DeepLogo (VGG)
Object DetectionFlickrLogos-32MAP73.5DeepLogo (AlexNet)
Image ClassificationFlickrLogos-32Accuracy89.6DeepLogo (GoogLeNet-GP)
3DFlickrLogos-32MAP74.4DeepLogo (VGG)
3DFlickrLogos-32MAP73.5DeepLogo (AlexNet)
2D ClassificationFlickrLogos-32MAP74.4DeepLogo (VGG)
2D ClassificationFlickrLogos-32MAP73.5DeepLogo (AlexNet)
2D Object DetectionFlickrLogos-32MAP74.4DeepLogo (VGG)
2D Object DetectionFlickrLogos-32MAP73.5DeepLogo (AlexNet)
16kFlickrLogos-32MAP74.4DeepLogo (VGG)
16kFlickrLogos-32MAP73.5DeepLogo (AlexNet)

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