This paper proposes a novel logo image recognition approach incorporating a
localization technique based on reinforcement learning. Logo recognition is an
image classification task identifying a brand in an image. As the size and
position of a logo vary widely from image to image, it is necessary to
determine its position for accurate recognition. However, because there is no
annotation for the position coordinates, it is impossible to train and infer
the location of the logo in the image. Therefore, we propose a deep
reinforcement learning localization method for logo recognition (RL-LOGO). It
utilizes deep reinforcement learning to identify a logo region in images
without annotations of the positions, thereby improving classification
accuracy. We demonstrated a significant improvement in accuracy compared with
existing methods in several published benchmarks. Specifically, we achieved an
18-point accuracy improvement over competitive methods on the complex dataset
Logo-2K+. This demonstrates that the proposed method is a promising approach to
logo recognition in real-world applications.

该论文提出了一种基于强化学习的定位技术的新型商标图像识别方法，它可以在没有位置注释的情况下利用深度强化学习来识别图像中的商标区域，从而提高分类准确性。该方法在多个基准测试中相比现有方法实现了显著的准确性改进，特别是在复杂数据集 Logo-2K + 上的准确性提升了 18 个百分点，证明了该方法在实际应用中具有很大的潜力。