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.

翻译：本文提出了一种融合强化学习定位技术的新型商标图像识别方法。商标识别是一项通过图像识别品牌的分类任务。由于商标在图像中的尺寸和位置差异显著，精确定位其位置是实现准确识别的必要条件。然而，由于缺乏位置坐标标注，无法对商标在图像中的位置进行训练与推理。为此，我们提出了一种基于深度强化学习的商标识别定位方法（RL-LOGO）。该方法利用深度强化学习在无需位置标注的情况下自动识别图像中的商标区域，从而提升分类准确率。在多个公开基准测试中，我们验证了该方法相较于现有算法具有显著的精度提升。具体而言，在复杂数据集Logo-2K+上，本方法的准确率较竞争算法提升了18个百分点。这表明所提方法在实际应用中是一种具有前景的商标识别方案。