As a class of historical relics, the importance of antiquarian documents is self-evident. In the process of digitizing these documents, due to uncontrollable factors such as physical deformation of the paper and position offset during camera capture, the photos often show different degrees of geometric distortion. Most document image unwarping models (Fig. 2.) can achieve the restoration of geometric distortion of the antiquarian document images. However, there has been lack of ancient document image unwarping datasets in academia, which makes it more difficult to propose and optimize models. To solve this dilemma, we construct the Antiquarian Document Image Unwarping dataset (ADIU), which covers most of the geometric distortion types. To the best of our knowledge, this is the first comprehensive and sizable document restoration dataset that can remove geometric and appearance distortion from camera images of antiquarian documents significantly, which contains 11,000 antiquarian document images.

Refinement of energy management in small- scale scenarios has been a hot research field in the past 10 years. An excellent algorithm can accurately infer the working condition and even the power consumption curve of every electrical appliance in a given period of time. Such information can not only help people to better control the working condition of the devices, but also improve the efficiency of energy use. From the perspective of algorithm research, an excellent dataset is essential to both the improvement of algorithm effect and the validation of algorithm efficiency; in the non-intrusive load research field, data is required to include as much information of the electrical devices as possible. Here we propose a new dataset, the Electrical Fingerprint Dataset (EFD). The data of the electrical fingerprint dataset is mainly collected from common household appliances and office devices. 126 common appliances are selected to form 15 data collection scenarios. Real and accurate annotation of the load decomposition results is obtained through synchronous acquisition of the current and voltage data at the bus and from every single device with a high frequency (1kHz). At the same time, information about the construction of the collection scenarios and the design and use of the hardware and software of special data-collection equipment, among others, will be introduced.