SalFAU-Net: Saliency Fusion Attention U-Net for Salient Object Detection

arXiv:2405.02906v1 Announce Type: new
Abstract: Salient object detection (SOD) remains an important task in computer vision, with applications ranging from image segmentation to autonomous driving. Fully convolutional network (FCN)-based methods have made remarkable progress in visual saliency detection over the last few decades. However, these methods have limitations in accurately detecting salient objects, particularly in challenging scenes with multiple objects, small objects, or objects with low resolutions. To address this issue, we proposed a Saliency Fusion Attention U-Net (SalFAU-Net) model, …

abstract applications arxiv attention autonomous autonomous driving computer computer vision convolutional cs.cv detection driving fusion however image limitations network object progress segmentation type vision visual