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Revise-Net: Exploiting Reverse Attention Mechanism for Salient Object Detection
2021
Remote Sensing
Recently, deep learning-based methods, especially utilizing fully convolutional neural networks, have shown extraordinary performance in salient object detection. Despite its success, the clean boundary detection of the saliency objects is still a challenging task. Most of the contemporary methods focus on exclusive edge detection modules in order to avoid noisy boundaries. In this work, we propose leveraging on the extraction of finer semantic features from multiple encoding layers and
doi:10.3390/rs13234941
fatcat:4jno22evrvehbm4zznwfi43yp4