Regional attention based multi-scale feature fusion for image retrieval

With the development of deep learning techniques, computer vision techniques have also been significantly improved. Image retrieval is a common technique used to retrieve images of interest from image databases, which can help users find the desired images more quickly. However, traditional image retrieval methods often fail to meet user needs because they often ignore complex scale information, e.g., features may differ at different scales. Therefore, an image retrieval based on a region-attention feature fusion mechanism can overcome this drawback, and it can improve the performance of image retrieval by emphasizing multi-scale features through a region-attention mechanism. In this paper, we propose an image retrieval method based on regional attention based multi-scale feature fusion, which can effectively use multiscale features. The effectiveness of RMFF is demonstrated by conducting experiments on mainstream image retrieval datasets.