<p>When capturing images through glass surfaces, it is inevitable to include reflections in acquired images. Such reflections not only degrade the aesthetic quality of the captured image but also adversely impact the performance of subsequent computer vision tasks. Residual reflections and artifacts still remain in the results, even though existing reflection removal algorithms are able to remove part of the reflection interference. Motivated by the observation that reflected objects present in input image are absent in corresponding ground-truth (reflection-free) image, this study proposes a reflection location awareness (RLA) approach for single image reflection removal. The proposed RLA method first detects reflection regions in the input image, generating an explicit representation of reflection locations. The representation is then leveraged as spatial prior information and fed into subsequent network modules, along with the input image, to recover texture details of background transmission layer. Extensive qualitative and quantitative experiments conducted on multiple benchmark datasets validate the effectiveness of the proposed method.</p>