One Shot Object Detection

One-Shot Object Detection is a sub-task in the field of computer vision that aims to achieve rapid detection and recognition of new categories through a single sample instance. The goal of this task is to enhance the model's generalization ability for unknown objects with limited annotated data, thereby reducing training costs and time in practical applications. Its application value lies in effectively addressing dynamically changing environments, making it suitable for real-time monitoring, intelligent security, and other scenarios.