Dataset is an important part of semantic segmentation technology based on deep learning. In order to apply semantic segmentation technology to the field battlefield environment, it is very important to construct a dataset that conforms to the actual combat scene. In this work, aiming at the operational support requirements for the detection and identification of camouflage targets, the characteristics of the field battlefield environment and battlefield reconnaissance images are analyzed, the construction process and method of the specific scene dataset are designed, and the semantic segmentation dataset CSS with refined semantic annotation is constructed. The effectiveness of the dataset on semantic segmentation tasks is verified by experiments.