As we have made a good number of improvements in our visual recommendation technology we decided to benchmark it against other popular deep learning networks. The aim was to compare our recommendation against AlexNet (Caffe implementation) and ResNet (Torch implementation) and to outline errors in product similarity identification. The setup for the comparison was such that with each network we fed in 3 different product categories and identified visually similar products based on a single thumbnail image. The errors are outlined in the images below in red circles. For the product categories we used 3260 different bags, 7028 different shoes