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Places365 CNNs

Convolutional neural networks (CNNs) trained on the Places2 Database can be used for scene recognition as well as generic deep scene features for visual recognition. We share the following pre-trained CNNs using Caffe deep learning toolbox. For each CNN, we provide the network deploy file, the trained network model, the list of scene categories and the train-val file which can be easily loaded using Caffe. Please cite our Places2 paper if you use these CNNs.

 

Here we release the data of Places365-Standard and the data of Places365-Challenge to the public. Places365-Standard is the core set of Places2 Database, which has been used to train the Places365-CNNs. We will add other kinds of annotation on the Places365-Standard in the future. Places365-Challenge is the competition set of Places2 Database, which has 6.2 million extra images compared to the Places365-Standard. The Places365-Challenge will be used for the Places Challenge 2016.

Data of Places365-Standard

There are 1.6 million train images from 365 scene categories in the Places365-Standard, which are used to train the Places365 CNNs. There are 50 images per category in the validation set and 900 images per category in the testing set.

 

Data of Places365-Challenge 2016

Compared to the train set of Places365-Standard, the train set of Places365-Challenge has 6.2 million extra images, leading to totally 8 million train images for the Places365 challenge 2016. The validation set and testing set are the same as the Places365-Standard.