iSAID is a large-scale dataset for instance segmentation in aerial images. It is the first benchmark dataset for instance segmentation in aerial images, combining instance-level object detection and pixel-level segmentation tasks. The dataset contains 2,806 high-resolution images of 655,451 object instances in 15 categories. The images of iSAID are the same as those of the DOTA-v1.0 dataset, and the data comes from Google Earth, JL-1 satellite, and GF-2 satellite (China Resources Satellite Data and Application Center).