MIT Places

by Bolei ZhouUnknown

MIT Places

We introduce a new scene-centric database called Places, with 205 scene categories and 2.5 millions of images with a category label. Using convolutional neural network (CNN), we learn deep scene features for scene recognition tasks, and establish new state-of-the-art performances on scene-centric benchmarks. Here we provide the Places Database and the trained CNNs for academic research and education purposes.

Dataset Attributes

Label SVG
TasksClassification
Label SVG
CategoriesBuildings, Humans, Nature, Vehicles, Airplanes
Label SVG
SensorRGB Camera

Class Labels

aquariumamusement parkarcadebasementbathroomclassroomindustrial park