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arXiv · 1610.02055

Places: An Image Database for Deep Scene Understanding

Bolei Zhou·Aditya Khosla·Agata Lapedriza·Antonio Torralba·Aude Oliva
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Abstract

The rise of multi-million-item dataset initiatives has enabled data-hungry machine learning algorithms to reach near-human semantic classification at tasks such as object and scene recognition. Here we describe the Places Database, a repository of 10 million scene photographs, labeled with scene semantic categories and attributes, comprising a quasi-exhaustive list of the types of environments encountered in the world. Using state of the art Convolutional Neural Networks, we provide impressive baseline performances at scene classification. With its high-coverage and high-diversity of exemplars, the Places Database offers an ecosystem to guide future progress on currently intractable visual recognition problems.

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Bolei Zhou, Aditya Khosla, Agata Lapedriza, Antonio Torralba, Aude Oliva. 2016-10-06. Places: An Image Database for Deep Scene Understanding. https://arxiv.org/abs/1610.02055

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