We present a novel multimodal dataset developed by expert astronomers to
automate the detection and localisation of multi-component extended radio
galaxies and their corresponding infrared hosts. The dataset comprises 4,155
instances of galaxies in 2,800 images with both radio and infrared modalities.
Each instance contains information on the extended radio galaxy class, its
corresponding bounding box that encompasses all of its components, pixel-level
segmentation mask, and the position of its corresponding infrared host galaxy.
Our dataset is the first publicly accessible dataset that includes images from
a highly sensitive radio telescope, infrared satellite, and instance-level
annotations for their identification. We benchmark several object detection
algorithms on the dataset and propose a novel multimodal approach to identify
radio galaxies and the positions of infrared hosts simultaneously.

我们提供了一个新颖的多模态数据集，由专家天文学家开发，用于自动检测和定位多组件扩展射电星系及其对应的红外主机。该数据集包括 2,800 个射电和红外模态图像中的 4,155 个星系实例。每个实例都包含有关扩展射电星系类别、包围其所有组件的边界框、像素级分割掩模以及其对应红外主机星系的位置的信息。我们的数据集是第一个公开可访问的数据集，包括来自高灵敏度射电望远镜、红外卫星以及用于其识别的实例级注释的图像。我们在数据集上对几种目标检测算法进行了基准测试，并提出了一种新颖的多模态方法，可以同时识别射电星系和红外主机的位置。