TCDCN facial landmark detection network, netscope: http://ethereon.github.io/netscope/#/gist/ee13b7dc668c126b75a63744ea0590b1

tcdcn-4conv.prototxt

name: "tcdcn_conv4_landmarks"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 48
  dim: 48
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 20
    pad: 0
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std:  0.01
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}

layer {
  name: "pool1"
  type:  "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 48
    pad: 0
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std:  0.01
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}

layer {
  name: "pool2"
  type:  "Pooling"
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  name: "conv3"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std:  0.01
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}

layer {
  name: "pool3"
  type:  "Pooling"
  bottom: "conv3"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}


layer {
  name: "conv4"
  type: "Convolution"
  bottom: "pool3"
  top: "conv4"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 80
    pad: 0
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std:  0.01
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}



layer {
  name: "fc5"
  type: "InnerProduct"
  bottom: "conv4"
  top: "fc5"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 1
  }

  inner_product_param {
    num_output: 256
    weight_filler {
     type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }

}


layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "fc5"
  top: "fc6"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 1
  }

  inner_product_param {
    num_output: 10
    weight_filler {
     type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }

}