Foreground Instance Segmentation

Foreground instance segmentation aims to precisely identify and delineate individual objects within an image or video, separating them from the background. Current research emphasizes improving robustness and generalization, particularly through the use of temporal context in video segmentation and techniques like visual prompting and self-supervised learning to reduce reliance on large annotated datasets. These advancements are driving progress in diverse applications, including video editing, anomaly detection, and open-world object recognition, by enabling more accurate and efficient object identification and manipulation.