Graph-Based Neural Networks for Explainable Image Privacy Inference

•We propose an improved dataset for research on image privacy.•We build a knowledge graph that represents the relevance between the objects and image privacy.•Based on the graph, we deal with the traditional image classification problem with the novel graph-based neural network.•The introduction of the knowledge graph not only makes the model more explainable but also makes better use of the information of objects provided by the images.•Our method relies on the intrinsic relevance in the dataset rather than extra knowledge, thus is applicable for other tasks.