BIG is a high-resolution semantic segmentation dataset containing 50 validation objects and 100 test objects. The image resolution of BIG ranges from 2048×1600 to 5000×3600, and each image is annotated by professionals, following the same guidelines as the PASCAL VOC 2012 dataset, with no blank areas.