One Shot Segmentation

One-Shot Segmentation is a subtask in the field of computer vision that aims to achieve pixel-level segmentation of new categories through a single sample. The goal of this task is to rapidly and accurately identify and segment specific objects in images with only a small amount of labeled data, demonstrating efficient learning and generalization capabilities. Its application value lies in significantly reducing the cost of large-scale data annotation and enhancing the model's adaptability and practicality in new scenarios.