Papers › DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer

DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer

7 Oct 2015arXiv:1510.02131archive 2025-07-28

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

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.

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Tasks

2D Object DetectionImage ClassificationLogo RecognitionObject DetectionObject Recognition

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Classification FlickrLogos-32 DeepLogo (GoogLeNet-GP) Accuracy 89.6 #3 of 3 Archive leaderboard report
Object Detection FlickrLogos-32 DeepLogo (VGG) MAP 74.4 #2 of 3 Archive leaderboard report
Object Detection FlickrLogos-32 DeepLogo (AlexNet) MAP 73.5 #3 of 3 Archive leaderboard report

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