A foreground attention map is a spatial feature representation generated by neural network attention mechanisms that selectively highlights target objects or regions of primary interest in an image while suppressing background areas. In computer vision tasks such as image segmentation and object detection, this map assigns higher numerical weights or activation values to pixels and regions corresponding to the interior and features of foreground entities. By directing model capacity toward salient or task-relevant visual cues, foreground attention maps facilitate accurate feature extraction, assist in delineating boundaries between objects and their surrounding environments, and improve the localization of ambiguous or camouflaged targets.
