GRAD-CAM Aware Supervised Attention For Visual Question Answering For Post-Disaster Damage Assessment

Single image reflection removal is a crucial technique which can improve the performance of object detection, semantic segmentation, and various computer vision applications. in this paper, we present a novel reflection removal algorithm using bi-channel priors (i.e., the dark channel prior and the bright channel prior). We observe that the values of dark channel pixels are not near 0, and those of bright channel pixels are not closer to 1 under the reflection scenario. We first demonstrate these phenomena statistically and mathematically. Then, we apply these properties as constraints in the optimization of the proposed reflection removal process. Extensive experiments on several well-known benchmarks demonstrate that our approach achieves desirable reflection suppression results compared with other methods.