DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer

2015/10/07 by Forrest Iandola, Anting Shen, Iandola, Forrest N. +5 · 2 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face recognition and analysis #Handwritten Text Recognition Techniques

paper · pdf · doi:10.48550/arxiv.1510.02131

openalex publication_date 2015/10/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Very Deep Convolutional Networks for Large-Scale Image Recognition
• DeCAF: A Deep Convolutional Activation Feature for Generic Visual\n Recognition
• Caffe: Convolutional Architecture for Fast Feature Embedding
• CNN Features off-the-shelf: an Astounding Baseline for Recognition

Cited by

• Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection
• Scalable Deep Learning Logo Detection

Related

• LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks
• Deep Learning for Logo Detection: A Survey
• Comparative Analysis of Deep Learning Models for Brand Logo Classification in Real-World Scenarios
• Scalable Logo Recognition using Proxies
• Automatic Graphic Logo Detection via Fast Region-based Convolutional\n Networks