Matterport, a company that builds 3D models of physical spaces for use in real estate, construction, and other industries, has publishes the Matterport 3D dataset, a collection of 10,800 3D models. Matterport worked with groups at Stanford University, Princeton University, and the Technical University of Munich to extensively annotate the dataset so that it can be used as training data to help AI systems better interpret 3D spaces.
Publishing 3D Data for AI Image Recognition
Joshua New is a policy analyst at the Center for Data Innovation. He has a background in government affairs, policy, and communication. Prior to joining the Center for Data Innovation, Joshua graduated from American University with degrees in C.L.E.G. (Communication, Legal Institutions, Economics, and Government) and Public Communication. His research focuses on methods of promoting innovative and emerging technologies as a means of improving the economy and quality of life. Follow Joshua on Twitter @Josh_A_New.