Link to A Survey for Multi-modal Knowledge Graphs.
Papers integrating Knowledge Graphs (KGs) and Multi-Modal Learning, focusing on research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph (MM4KG), which extends KG studies into the MMKG realm.
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MMKG is a collection of three knowledge graphs for link prediction and entity matching research. Contrary to other knowledge graph datasets, these knowledge graphs contain both numerical features and images for all entities as well as entity alignments between pairs of KGs. While MMKG is intended to perform relational reasoning across different entities and images, previous resources are intended to perform visual reasoning within the same image. The three knowledge graphs augmented with numerical features and images are called FB15k, YAGO15k, and DBPEDIA15k.
VirtualHome2KG is a system for constructing and augmenting knowledge graphs (KGs) of daily living activities using virtual space. We also provide an ontology to describe the structure of the KGs. We used VirtualHome as a platform of virtual space simulation. Thus, this repository is an extension of the virtualhome. Please see the original repository of the virtualhome for details of the Unity simulation.