WebLogo-2M: Scalable Logo Detection by Deep Learning from the Web

@article{Su2017WebLogo2MSL,
  title={WebLogo-2M: Scalable Logo Detection by Deep Learning from the Web},
  author={Hang Su and Shaogang Gong and Xiatian Zhu},
  journal={2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},
  year={2017},
  pages={270-279}
}
Existing logo detection methods usually consider a small number of logo classes and limited images per class with a strong assumption of requiring tedious object bounding box annotations, therefore not scalable to real-world applications. In this work, we tackle these challenges by exploring the webly data learning principle without the need for exhaustive manual labelling. Specifically, we propose a novel incremental learning approach, called Scalable Logo Self-Training (SLST), capable of… CONTINUE READING

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