This a MxNet implementation of DenseNet-BC architecture as described in the paper Densely Connected Convolutional Networks by Gao Huang, Zhuang Liu, Kilian Q. Weinberger, Laurens van der Maaten.
This implementation only focus on imagenet'12 dataset. The training procedure is ongoing. So, I hope anyone who are mxnet fun can test this code with me. When I finish, I will update more information about training and validation.
Their official implementation and many other third-party implementations can be found in the liuzhuang13/DenseNet repo on GitHub.
This is a basic dense block (figure is modified from the original paper). Each layer takes all preceding feature maps as input. It is a very interesting and simple design.
