Few-Shot Object Detection

Few-Shot Object Detection is a task in the field of computer vision that aims to detect objects in images using limited training data. The core objective of this task is to train a model with only a few samples per object category so that it can effectively identify similar objects in new images. This technology is of significant application value in reducing the need for annotated data and enhancing model adaptability.