##Information
name: CNN_S model from the BMVC-2014 paper: "Return of the Devil in the Details: Delving Deep into Convolutional Nets"
mean_file_mat: http://www.robots.ox.ac.uk/~vgg/software/deep_eval/releases/bvlc/VGG_mean.mat
mean_file_proto: http://www.robots.ox.ac.uk/~vgg/software/deep_eval/releases/bvlc/VGG_mean.binaryproto
caffemodel: VGG_CNN_S
caffemodel_url: http://www.robots.ox.ac.uk/~vgg/software/deep_eval/releases/bvlc/VGG_CNN_S.caffemodel
license: non-commercial use only
caffe_version: trained using a custom Caffe-based framework
gist_id: fd8800eeb36e276cd6f9
The CNN_S model is trained on the ILSVRC-2012 dataset. The details can be found in the following BMVC-2014 paper:
Return of the Devil in the Details: Delving Deep into Convolutional Nets
K. Chatfield, K. Simonyan, A. Vedaldi, A. Zisserman
British Machine Vision Conference, 2014 (arXiv ref. cs1405.3531)
Please cite the paper if you use the model.
The model is trained on 224x224 crops sampled from images, rescaled so that the smallest side is 256 (preserving the aspect ratio). The released mean BGR image should be subtracted from 224x224 crops.
Further details can be found in the paper and on the project website: http://www.robots.ox.ac.uk/~vgg/research/deep_eval/
The model is stored in a different format than the one released at http://www.robots.ox.ac.uk/~vgg/software/deep_eval/ to make it compatible with BVLC Caffe and BGR images (the network weights are the same). The class order is also different; the one used here corresponds to synsets.txt in http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz
Using 10 test crops (corners, centre, and horizontal flips), the top-5 classification error on the validation set of ILSVRC-2012 is 13.1%.
Using a single central crop, the top-5 classification error on the validation set of ILSVRC-2012 is 15.4%
The details of the evaluation can be found in the paper.
could you give us you train_val.prototxt?