Context-Based Synthetic Data for Logo Recognition

In order to solve the problem of sparse training samples in logo recognition task, a multi-type context-based logo data synthesis algorithm is proposed. The algorithm comprehensively utilizes the local and full context of the logo object and the scene image to guide the synthesis of the logo image. The experimental results on the FlickrLogos-32 show that the proposed algorithm can greatly improve the performance of the logo recognition algorithm without relying on additional manual annotation, verify the validity of the synthesis algorithm, and further prove that multi-type context can improve the performance of the object recognition algorithm.