name: "Heatmap_3dJoint"


input: "depth"
input_dim: 1
input_dim: 1
input_dim: 180
input_dim: 240


input: "heatmaps_point"
input_dim: 1
input_dim: 16
input_dim: 30
input_dim: 40


layer {
  name: "depth_convL0"
  type: "Convolution"
  bottom: "depth"
  top: "depth_convL0"
  convolution_param {
    num_output: 16	
    kernel_size: 3
	pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "depth_ReLUconvL0"
  type: "ReLU"
  bottom: "depth_convL0"
  top: "depth_convL0"
}


layer {
  name: "depth_poolL0"
  type: "Pooling"
  bottom: "depth_convL0"
  top: "depth_poolL0"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}



layer {
  name: "depth_convL1"
  type: "Convolution"
  bottom: "depth_poolL0"
  top: "depth_convL1"
  convolution_param {
    num_output: 32	
    kernel_size: 3
	pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "ReLUdepth_convL1"
  type: "ReLU"
  bottom: "depth_convL1"
  top: "depth_convL1"
}


layer {
  name: "depth_poolL1"
  type: "Pooling"
  bottom: "depth_convL1"
  top: "depth_poolL1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 3
  }
}



layer {
  name: "depth_convL2"
  type: "Convolution"
  bottom: "depth_poolL1"
  top: "depth_convL2"
  convolution_param {
    num_output: 64
    kernel_size: 3
	pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}


layer {
  name: "ReLUdepth_convL2"
  type: "ReLU"
  bottom: "depth_convL2"
  top: "depth_convL2"
}


layer {
  name: "depth_convL3"
  type: "Convolution"
  bottom: "depth_convL2"
  top: "depth_convL3"
  convolution_param {
    num_output: 64
    kernel_size: 3
	pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "depth_ReLUconvL3"
  type: "ReLU"
  bottom: "depth_convL3"
  top: "depth_convL3"
}

layer {
  name: "depth_convL5"
  type: "Convolution"
  bottom: "depth_convL3"
  top: "depth_convL5"
  convolution_param {
    num_output: 48
    kernel_size: 3
	pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "depth_ReLUconvL5"
  type: "ReLU"
  bottom: "depth_convL5"
  top: "depth_convL5"
}




layer {
  name: "concat_heatmaps_point"
  type: "Concat"
  bottom: "heatmaps_point"
  bottom: "heatmaps_point"
  bottom: "heatmaps_point"
  top: "concat_heatmaps_point"
  concat_param {
    axis: 1
  }
}


layer {
  name: "mul_feature"
  type: "Eltwise"
  bottom: "concat_heatmaps_point"
  bottom: "depth_convL5"
  top: "mul_feature"
  eltwise_param {
    operation: PROD
  }
}



layer {
  name: "stage1_conv1_L2"
  type: "Convolution"
  bottom: "mul_feature"
  top: "stage1_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage1_relu1_L2"
  type: "ReLU"
  bottom: "stage1_conv1_L2"
  top: "stage1_conv1_L2"
}

layer {
  name: "stage1_conv2_L2"
  type: "Convolution"
  bottom: "stage1_conv1_L2"
  top: "stage1_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage1_relu2_L2"
  type: "ReLU"
  bottom: "stage1_conv2_L2"
  top: "stage1_conv2_L2"
}






layer {
  name: "stage1_conv3_L2"
  type: "Convolution"
  bottom: "stage1_conv2_L2"
  top: "stage1_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage1_relu3_L2"
  type: "ReLU"
  bottom: "stage1_conv3_L2"
  top: "stage1_conv3_L2"
}



layer {
  name: "stage1_conv4_L2"
  type: "Convolution"
  bottom: "stage1_conv3_L2"
  top: "stage1_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage1_relu4_L2"
  type: "ReLU"
  bottom: "stage1_conv4_L2"
  top: "stage1_conv4_L2"
}



layer {
  name: "stage1_conv5_L2"
  type: "Convolution"
  bottom: "stage1_conv4_L2"
  top: "stage1_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}


layer {
  name: "concat_stage2"
  type: "Concat"
  bottom: "stage1_conv5_L2"
  bottom: "mul_feature"
  top: "concat_stage2"
  concat_param {
    axis: 1
  }
}



layer {
  name: "stage2_conv1_L2"
  type: "Convolution"
  bottom: "concat_stage2"
  top: "stage2_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage2_relu1_L2"
  type: "ReLU"
  bottom: "stage2_conv1_L2"
  top: "stage2_conv1_L2"
}

layer {
  name: "stage2_conv2_L2"
  type: "Convolution"
  bottom: "stage2_conv1_L2"
  top: "stage2_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage2_relu2_L2"
  type: "ReLU"
  bottom: "stage2_conv2_L2"
  top: "stage2_conv2_L2"
}






layer {
  name: "stage2_conv3_L2"
  type: "Convolution"
  bottom: "stage2_conv2_L2"
  top: "stage2_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage2_relu3_L2"
  type: "ReLU"
  bottom: "stage2_conv3_L2"
  top: "stage2_conv3_L2"
}



layer {
  name: "stage2_conv4_L2"
  type: "Convolution"
  bottom: "stage2_conv3_L2"
  top: "stage2_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage2_relu4_L2"
  type: "ReLU"
  bottom: "stage2_conv4_L2"
  top: "stage2_conv4_L2"
}



layer {
  name: "stage2_conv5_L2"
  type: "Convolution"
  bottom: "stage2_conv4_L2"
  top: "stage2_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}




layer {
  name: "concat_stage3"
  type: "Concat"
  bottom: "stage2_conv5_L2"
  bottom: "mul_feature"
  top: "concat_stage3"
  concat_param {
    axis: 1
  }
}



layer {
  name: "stage3_conv1_L2"
  type: "Convolution"
  bottom: "concat_stage3"
  top: "stage3_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage3_relu1_L2"
  type: "ReLU"
  bottom: "stage3_conv1_L2"
  top: "stage3_conv1_L2"
}

layer {
  name: "stage3_conv2_L2"
  type: "Convolution"
  bottom: "stage3_conv1_L2"
  top: "stage3_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage3_relu2_L2"
  type: "ReLU"
  bottom: "stage3_conv2_L2"
  top: "stage3_conv2_L2"
}






layer {
  name: "stage3_conv3_L2"
  type: "Convolution"
  bottom: "stage3_conv2_L2"
  top: "stage3_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage3_relu3_L2"
  type: "ReLU"
  bottom: "stage3_conv3_L2"
  top: "stage3_conv3_L2"
}



layer {
  name: "stage3_conv4_L2"
  type: "Convolution"
  bottom: "stage3_conv3_L2"
  top: "stage3_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage3_relu4_L2"
  type: "ReLU"
  bottom: "stage3_conv4_L2"
  top: "stage3_conv4_L2"
}



layer {
  name: "stage3_conv5_L2"
  type: "Convolution"
  bottom: "stage3_conv4_L2"
  top: "stage3_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}



layer {
  name: "concat_stage4"
  type: "Concat"
  bottom: "stage3_conv5_L2"
  bottom: "mul_feature"
  top: "concat_stage4"
  concat_param {
    axis: 1
  }
}



layer {
  name: "stage4_conv1_L2"
  type: "Convolution"
  bottom: "concat_stage4"
  top: "stage4_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage4_relu1_L2"
  type: "ReLU"
  bottom: "stage4_conv1_L2"
  top: "stage4_conv1_L2"
}

layer {
  name: "stage4_conv2_L2"
  type: "Convolution"
  bottom: "stage4_conv1_L2"
  top: "stage4_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage4_relu2_L2"
  type: "ReLU"
  bottom: "stage4_conv2_L2"
  top: "stage4_conv2_L2"
}






layer {
  name: "stage4_conv3_L2"
  type: "Convolution"
  bottom: "stage4_conv2_L2"
  top: "stage4_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage4_relu3_L2"
  type: "ReLU"
  bottom: "stage4_conv3_L2"
  top: "stage4_conv3_L2"
}



layer {
  name: "stage4_conv4_L2"
  type: "Convolution"
  bottom: "stage4_conv3_L2"
  top: "stage4_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage4_relu4_L2"
  type: "ReLU"
  bottom: "stage4_conv4_L2"
  top: "stage4_conv4_L2"
}



layer {
  name: "stage4_conv5_L2"
  type: "Convolution"
  bottom: "stage4_conv4_L2"
  top: "stage4_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}



layer {
  name: "concat_stage5"
  type: "Concat"
  bottom: "stage4_conv5_L2"
  bottom: "mul_feature"
  top: "concat_stage5"
  concat_param {
    axis: 1
  }
}



layer {
  name: "stage5_conv1_L2"
  type: "Convolution"
  bottom: "concat_stage5"
  top: "stage5_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage5_relu1_L2"
  type: "ReLU"
  bottom: "stage5_conv1_L2"
  top: "stage5_conv1_L2"
}

layer {
  name: "stage5_conv2_L2"
  type: "Convolution"
  bottom: "stage5_conv1_L2"
  top: "stage5_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage5_relu2_L2"
  type: "ReLU"
  bottom: "stage5_conv2_L2"
  top: "stage5_conv2_L2"
}






layer {
  name: "stage5_conv3_L2"
  type: "Convolution"
  bottom: "stage5_conv2_L2"
  top: "stage5_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage5_relu3_L2"
  type: "ReLU"
  bottom: "stage5_conv3_L2"
  top: "stage5_conv3_L2"
}



layer {
  name: "stage5_conv4_L2"
  type: "Convolution"
  bottom: "stage5_conv3_L2"
  top: "stage5_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage5_relu4_L2"
  type: "ReLU"
  bottom: "stage5_conv4_L2"
  top: "stage5_conv4_L2"
}



layer {
  name: "stage5_conv5_L2"
  type: "Convolution"
  bottom: "stage5_conv4_L2"
  top: "stage5_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}



layer {
  name: "concat_stage6"
  type: "Concat"
  bottom: "stage5_conv5_L2"
  bottom: "mul_feature"
  top: "concat_stage6"
  concat_param {
    axis: 1
  }
}



layer {
  name: "stage6_conv1_L2"
  type: "Convolution"
  bottom: "concat_stage6"
  top: "stage6_conv1_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage6_relu1_L2"
  type: "ReLU"
  bottom: "stage6_conv1_L2"
  top: "stage6_conv1_L2"
}

layer {
  name: "stage6_conv2_L2"
  type: "Convolution"
  bottom: "stage6_conv1_L2"
  top: "stage6_conv2_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage6_relu2_L2"
  type: "ReLU"
  bottom: "stage6_conv2_L2"
  top: "stage6_conv2_L2"
}






layer {
  name: "stage6_conv3_L2"
  type: "Convolution"
  bottom: "stage6_conv2_L2"
  top: "stage6_conv3_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage6_relu3_L2"
  type: "ReLU"
  bottom: "stage6_conv3_L2"
  top: "stage6_conv3_L2"
}



layer {
  name: "stage6_conv4_L2"
  type: "Convolution"
  bottom: "stage6_conv3_L2"
  top: "stage6_conv4_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "stage6_relu4_L2"
  type: "ReLU"
  bottom: "stage6_conv4_L2"
  top: "stage6_conv4_L2"
}



layer {
  name: "stage6_conv5_L2"
  type: "Convolution"
  bottom: "stage6_conv4_L2"
  top: "stage6_conv5_L2"
  param {
    lr_mult: 1.0
    decay_mult: 1
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}