Saliency and Detail Map Interactive Model for Salient Region Detection
Yu-Yao Huang, Jian–Jiun Ding, Shiang–Chih Hua · 2023
Salient object detection (SOD) is a preprocessing step for several computer vision techniques, including visual tracking, image captioning, image segmentation, and so on. In this work, several techniques are adopted to improve the accuracy of SOD. Instead of directly using edge maps as guidance, we improve the adaptive two-stream encoder by employing a clever technique to generate body maps and detail maps, which can provide much information for the final predictions. Regarding body maps and detail maps, different parameter contrasts are provided for users to choose the desired results. Compared to state-of-the-art SOD algorithms, our method outperforms almost all other methods on twelve datasets under two evaluation metrics.