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Deep Learning for Logo Detection | IEEE Conference Publication | IEEE Xplore
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Deep Learning for Logo Detection


Abstract:

We present a deep learning system for automatic logo detection in real world images. We base our detector on the popular framework of FasterR-CNN and compare its performa...Show More

Abstract:

We present a deep learning system for automatic logo detection in real world images. We base our detector on the popular framework of FasterR-CNN and compare its performance to other models such as Mask R-CNN or RetinaNet. We perform a detailed empirical analysis of various design and architecture choices and show how these can have much higher influence than algorithmic tweaks or popular techniques such as data augmentation. We also provide a systematic detection performance comparison of various models on multiple popular datasets including FlickrLogos-32, TopLogo-10 and recently introduced QMUL-OpenLogo benchmark, which allows for a direct comparison between recently proposed extensions. By careful optimization of the training procedure we were able to achieve significant improvements of the state of the art on all mentioned datasets. We apply our observations to build a detector to detect logos of the Red Bull brand in online media and images.
Date of Conference: 01-03 July 2019
Date Added to IEEE Xplore: 25 July 2019
ISBN Information:
Conference Location: Budapest, Hungary

References

References is not available for this document.