Places: A 10 Million Image Database for Scene Recognition

The rise of multi-million-item dataset initiatives has enabled data-hungry machine learning algorithms to reach near-human semantic classification performance at tasks such as visual object and scene recognition. Here we describe the Places Database, a repository of 10 million scene photographs, labeled with scene semantic categories, comprising a large and diverse list of the types of environments encountered in the world. Using the state-of-the-art Convolutional Neural Networks (CNNs), we provide scene classification CNNs (Places-CNNs) as baselines, that significantly outperform the previous approaches. Visualization of the CNNs trained on Places shows that object detectors emerge as an intermediate…

• NS
  National Science Foundation

  Awards: 1524817, 1016862
• TR
  Toyota Research Institute
• OO
  Office of Naval Research

  Awards: N00014-16-1-3116 to A.O., N00014-16-1-3116, N00014