Created
January 12, 2020 11:18
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flownet1
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| input: "img0" | |
| input: "img1" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 720 | |
| dim: 1280 | |
| } | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 720 | |
| dim: 1280 | |
| } | |
| layer { | |
| name: "Eltwise1" | |
| type: "Eltwise" | |
| bottom: "img0" | |
| top: "img0s" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.00392156862745098 | |
| } | |
| } | |
| layer { | |
| name: "Eltwise2" | |
| type: "Eltwise" | |
| bottom: "img1" | |
| top: "img1s" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.00392156862745098 | |
| } | |
| } | |
| layer { | |
| name: "img0s_aug" | |
| type: "DataAugmentation" | |
| bottom: "img0s" | |
| top: "img0_nomean" | |
| augmentation_param { | |
| augment_during_test: true | |
| recompute_mean: 1000 | |
| mean_per_pixel: false | |
| } | |
| } | |
| layer { | |
| name: "img1s_aug" | |
| type: "DataAugmentation" | |
| bottom: "img1s" | |
| top: "img1_nomean" | |
| augmentation_param { | |
| augment_during_test: true | |
| recompute_mean: 1000 | |
| mean_per_pixel: false | |
| } | |
| } | |
| layer { | |
| name: "Resample1" | |
| type: "Resample" | |
| bottom: "img0_nomean" | |
| top: "img0_nomean_resize" | |
| resample_param { | |
| width: 1024 | |
| height: 768 | |
| type: LINEAR | |
| antialias: true | |
| } | |
| } | |
| layer { | |
| name: "Resample2" | |
| type: "Resample" | |
| bottom: "img1_nomean" | |
| top: "img1_nomean_resize" | |
| resample_param { | |
| width: 1024 | |
| height: 768 | |
| type: LINEAR | |
| antialias: true | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "img0_nomean_resize" | |
| bottom: "img1_nomean_resize" | |
| top: "conv1a" | |
| top: "conv1b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU1" | |
| type: "ReLU" | |
| bottom: "conv1a" | |
| top: "conv1a" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU2" | |
| type: "ReLU" | |
| bottom: "conv1b" | |
| top: "conv1b" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv1a" | |
| bottom: "conv1b" | |
| top: "conv2a" | |
| top: "conv2b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU3" | |
| type: "ReLU" | |
| bottom: "conv2a" | |
| top: "conv2a" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU4" | |
| type: "ReLU" | |
| bottom: "conv2b" | |
| top: "conv2b" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "conv2a" | |
| bottom: "conv2b" | |
| top: "conv3a" | |
| top: "conv3b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU5" | |
| type: "ReLU" | |
| bottom: "conv3a" | |
| top: "conv3a" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU6" | |
| type: "ReLU" | |
| bottom: "conv3b" | |
| top: "conv3b" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "corr" | |
| type: "Correlation" | |
| bottom: "conv3a" | |
| bottom: "conv3b" | |
| top: "corr" | |
| correlation_param { | |
| pad: 20 | |
| kernel_size: 1 | |
| max_displacement: 20 | |
| stride_1: 1 | |
| stride_2: 2 | |
| } | |
| } | |
| layer { | |
| name: "ReLU7" | |
| type: "ReLU" | |
| bottom: "corr" | |
| top: "corr" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv_redir" | |
| type: "Convolution" | |
| bottom: "conv3a" | |
| top: "conv_redir" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU8" | |
| type: "ReLU" | |
| bottom: "conv_redir" | |
| top: "conv_redir" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat1" | |
| type: "Concat" | |
| bottom: "conv_redir" | |
| bottom: "corr" | |
| top: "blob16" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "blob16" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU9" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU10" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU11" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU12" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Convolution" | |
| bottom: "conv5" | |
| top: "conv5_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU13" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU14" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "conv6_1" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv6_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU15" | |
| type: "ReLU" | |
| bottom: "conv6_1" | |
| top: "conv6_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Convolution1" | |
| type: "Convolution" | |
| bottom: "conv6_1" | |
| top: "predict_flow6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "deconv5" | |
| type: "Deconvolution" | |
| bottom: "conv6_1" | |
| top: "deconv5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU16" | |
| type: "ReLU" | |
| bottom: "deconv5" | |
| top: "deconv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow6to5" | |
| type: "Deconvolution" | |
| bottom: "predict_flow6" | |
| top: "upsampled_flow6_to_5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat2" | |
| type: "Concat" | |
| bottom: "conv5_1" | |
| bottom: "deconv5" | |
| bottom: "upsampled_flow6_to_5" | |
| top: "concat5" | |
| } | |
| layer { | |
| name: "Convolution2" | |
| type: "Convolution" | |
| bottom: "concat5" | |
| top: "predict_flow5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "deconv4" | |
| type: "Deconvolution" | |
| bottom: "concat5" | |
| top: "deconv4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU17" | |
| type: "ReLU" | |
| bottom: "deconv4" | |
| top: "deconv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow5to4" | |
| type: "Deconvolution" | |
| bottom: "predict_flow5" | |
| top: "upsampled_flow5_to_4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat3" | |
| type: "Concat" | |
| bottom: "conv4_1" | |
| bottom: "deconv4" | |
| bottom: "upsampled_flow5_to_4" | |
| top: "concat4" | |
| } | |
| layer { | |
| name: "Convolution3" | |
| type: "Convolution" | |
| bottom: "concat4" | |
| top: "predict_flow4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "deconv3" | |
| type: "Deconvolution" | |
| bottom: "concat4" | |
| top: "deconv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU18" | |
| type: "ReLU" | |
| bottom: "deconv3" | |
| top: "deconv3" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow4to3" | |
| type: "Deconvolution" | |
| bottom: "predict_flow4" | |
| top: "upsampled_flow4_to_3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat4" | |
| type: "Concat" | |
| bottom: "conv3_1" | |
| bottom: "deconv3" | |
| bottom: "upsampled_flow4_to_3" | |
| top: "concat3" | |
| } | |
| layer { | |
| name: "Convolution4" | |
| type: "Convolution" | |
| bottom: "concat3" | |
| top: "predict_flow3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "deconv2" | |
| type: "Deconvolution" | |
| bottom: "concat3" | |
| top: "deconv2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU19" | |
| type: "ReLU" | |
| bottom: "deconv2" | |
| top: "deconv2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow3to2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow3" | |
| top: "upsampled_flow3_to_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat5" | |
| type: "Concat" | |
| bottom: "conv2a" | |
| bottom: "deconv2" | |
| bottom: "upsampled_flow3_to_2" | |
| top: "concat2" | |
| } | |
| layer { | |
| name: "Convolution5" | |
| type: "Convolution" | |
| bottom: "concat2" | |
| top: "predict_flow2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Eltwise3" | |
| type: "Eltwise" | |
| bottom: "predict_flow2" | |
| top: "blob41" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 20.0 | |
| } | |
| } | |
| layer { | |
| name: "Accum1" | |
| type: "Accum" | |
| bottom: "blob41" | |
| bottom: "img0_nomean_resize" | |
| top: "blob42" | |
| accum_param { | |
| have_reference: true | |
| } | |
| } | |
| layer { | |
| name: "FlowWarp1" | |
| type: "FlowWarp" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob42" | |
| top: "blob43" | |
| } | |
| layer { | |
| name: "Eltwise4" | |
| type: "Eltwise" | |
| bottom: "img0_nomean_resize" | |
| bottom: "blob43" | |
| top: "blob44" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1.0 | |
| coeff: -1.0 | |
| } | |
| } | |
| layer { | |
| name: "ChannelNorm1" | |
| type: "ChannelNorm" | |
| bottom: "blob44" | |
| top: "blob45" | |
| } | |
| layer { | |
| name: "Eltwise5" | |
| type: "Eltwise" | |
| bottom: "blob42" | |
| top: "blob46" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.05 | |
| } | |
| } | |
| layer { | |
| name: "Concat6" | |
| type: "Concat" | |
| bottom: "img0_nomean_resize" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob43" | |
| bottom: "blob46" | |
| bottom: "blob45" | |
| top: "blob47" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "net2_conv1" | |
| type: "Convolution" | |
| bottom: "blob47" | |
| top: "blob48" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU20" | |
| type: "ReLU" | |
| bottom: "blob48" | |
| top: "blob48" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv2" | |
| type: "Convolution" | |
| bottom: "blob48" | |
| top: "blob49" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU21" | |
| type: "ReLU" | |
| bottom: "blob49" | |
| top: "blob49" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv3" | |
| type: "Convolution" | |
| bottom: "blob49" | |
| top: "blob50" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU22" | |
| type: "ReLU" | |
| bottom: "blob50" | |
| top: "blob50" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv3_1" | |
| type: "Convolution" | |
| bottom: "blob50" | |
| top: "blob51" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU23" | |
| type: "ReLU" | |
| bottom: "blob51" | |
| top: "blob51" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv4" | |
| type: "Convolution" | |
| bottom: "blob51" | |
| top: "blob52" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU24" | |
| type: "ReLU" | |
| bottom: "blob52" | |
| top: "blob52" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv4_1" | |
| type: "Convolution" | |
| bottom: "blob52" | |
| top: "blob53" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU25" | |
| type: "ReLU" | |
| bottom: "blob53" | |
| top: "blob53" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv5" | |
| type: "Convolution" | |
| bottom: "blob53" | |
| top: "blob54" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU26" | |
| type: "ReLU" | |
| bottom: "blob54" | |
| top: "blob54" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv5_1" | |
| type: "Convolution" | |
| bottom: "blob54" | |
| top: "blob55" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU27" | |
| type: "ReLU" | |
| bottom: "blob55" | |
| top: "blob55" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv6" | |
| type: "Convolution" | |
| bottom: "blob55" | |
| top: "blob56" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU28" | |
| type: "ReLU" | |
| bottom: "blob56" | |
| top: "blob56" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_conv6_1" | |
| type: "Convolution" | |
| bottom: "blob56" | |
| top: "blob57" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU29" | |
| type: "ReLU" | |
| bottom: "blob57" | |
| top: "blob57" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_predict_conv6" | |
| type: "Convolution" | |
| bottom: "blob57" | |
| top: "blob58" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_deconv5" | |
| type: "Deconvolution" | |
| bottom: "blob57" | |
| top: "blob59" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU30" | |
| type: "ReLU" | |
| bottom: "blob59" | |
| top: "blob59" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_net2_upsample_flow6to5" | |
| type: "Deconvolution" | |
| bottom: "blob58" | |
| top: "blob60" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat7" | |
| type: "Concat" | |
| bottom: "blob55" | |
| bottom: "blob59" | |
| bottom: "blob60" | |
| top: "blob61" | |
| } | |
| layer { | |
| name: "net2_predict_conv5" | |
| type: "Convolution" | |
| bottom: "blob61" | |
| top: "blob62" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_deconv4" | |
| type: "Deconvolution" | |
| bottom: "blob61" | |
| top: "blob63" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU31" | |
| type: "ReLU" | |
| bottom: "blob63" | |
| top: "blob63" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_net2_upsample_flow5to4" | |
| type: "Deconvolution" | |
| bottom: "blob62" | |
| top: "blob64" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat8" | |
| type: "Concat" | |
| bottom: "blob53" | |
| bottom: "blob63" | |
| bottom: "blob64" | |
| top: "blob65" | |
| } | |
| layer { | |
| name: "net2_predict_conv4" | |
| type: "Convolution" | |
| bottom: "blob65" | |
| top: "blob66" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_deconv3" | |
| type: "Deconvolution" | |
| bottom: "blob65" | |
| top: "blob67" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU32" | |
| type: "ReLU" | |
| bottom: "blob67" | |
| top: "blob67" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_net2_upsample_flow4to3" | |
| type: "Deconvolution" | |
| bottom: "blob66" | |
| top: "blob68" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat9" | |
| type: "Concat" | |
| bottom: "blob51" | |
| bottom: "blob67" | |
| bottom: "blob68" | |
| top: "blob69" | |
| } | |
| layer { | |
| name: "net2_predict_conv3" | |
| type: "Convolution" | |
| bottom: "blob69" | |
| top: "blob70" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_deconv2" | |
| type: "Deconvolution" | |
| bottom: "blob69" | |
| top: "blob71" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU33" | |
| type: "ReLU" | |
| bottom: "blob71" | |
| top: "blob71" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net2_net2_upsample_flow3to2" | |
| type: "Deconvolution" | |
| bottom: "blob70" | |
| top: "blob72" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat10" | |
| type: "Concat" | |
| bottom: "blob49" | |
| bottom: "blob71" | |
| bottom: "blob72" | |
| top: "blob73" | |
| } | |
| layer { | |
| name: "net2_predict_conv2" | |
| type: "Convolution" | |
| bottom: "blob73" | |
| top: "blob74" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Eltwise6" | |
| type: "Eltwise" | |
| bottom: "blob74" | |
| top: "blob75" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 20.0 | |
| } | |
| } | |
| layer { | |
| name: "Accum2" | |
| type: "Accum" | |
| bottom: "blob75" | |
| bottom: "img0_nomean_resize" | |
| top: "blob76" | |
| accum_param { | |
| have_reference: true | |
| } | |
| } | |
| layer { | |
| name: "FlowWarp2" | |
| type: "FlowWarp" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob76" | |
| top: "blob77" | |
| } | |
| layer { | |
| name: "Eltwise7" | |
| type: "Eltwise" | |
| bottom: "img0_nomean_resize" | |
| bottom: "blob77" | |
| top: "blob78" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1.0 | |
| coeff: -1.0 | |
| } | |
| } | |
| layer { | |
| name: "ChannelNorm2" | |
| type: "ChannelNorm" | |
| bottom: "blob78" | |
| top: "blob79" | |
| } | |
| layer { | |
| name: "Eltwise8" | |
| type: "Eltwise" | |
| bottom: "blob76" | |
| top: "blob80" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.05 | |
| } | |
| } | |
| layer { | |
| name: "Concat11" | |
| type: "Concat" | |
| bottom: "img0_nomean_resize" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob77" | |
| bottom: "blob80" | |
| bottom: "blob79" | |
| top: "blob81" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "net3_conv1" | |
| type: "Convolution" | |
| bottom: "blob81" | |
| top: "blob82" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU34" | |
| type: "ReLU" | |
| bottom: "blob82" | |
| top: "blob82" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv2" | |
| type: "Convolution" | |
| bottom: "blob82" | |
| top: "blob83" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU35" | |
| type: "ReLU" | |
| bottom: "blob83" | |
| top: "blob83" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv3" | |
| type: "Convolution" | |
| bottom: "blob83" | |
| top: "blob84" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU36" | |
| type: "ReLU" | |
| bottom: "blob84" | |
| top: "blob84" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv3_1" | |
| type: "Convolution" | |
| bottom: "blob84" | |
| top: "blob85" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU37" | |
| type: "ReLU" | |
| bottom: "blob85" | |
| top: "blob85" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv4" | |
| type: "Convolution" | |
| bottom: "blob85" | |
| top: "blob86" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU38" | |
| type: "ReLU" | |
| bottom: "blob86" | |
| top: "blob86" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv4_1" | |
| type: "Convolution" | |
| bottom: "blob86" | |
| top: "blob87" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU39" | |
| type: "ReLU" | |
| bottom: "blob87" | |
| top: "blob87" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv5" | |
| type: "Convolution" | |
| bottom: "blob87" | |
| top: "blob88" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU40" | |
| type: "ReLU" | |
| bottom: "blob88" | |
| top: "blob88" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv5_1" | |
| type: "Convolution" | |
| bottom: "blob88" | |
| top: "blob89" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU41" | |
| type: "ReLU" | |
| bottom: "blob89" | |
| top: "blob89" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv6" | |
| type: "Convolution" | |
| bottom: "blob89" | |
| top: "blob90" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU42" | |
| type: "ReLU" | |
| bottom: "blob90" | |
| top: "blob90" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_conv6_1" | |
| type: "Convolution" | |
| bottom: "blob90" | |
| top: "blob91" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU43" | |
| type: "ReLU" | |
| bottom: "blob91" | |
| top: "blob91" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_predict_conv6" | |
| type: "Convolution" | |
| bottom: "blob91" | |
| top: "blob92" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_deconv5" | |
| type: "Deconvolution" | |
| bottom: "blob91" | |
| top: "blob93" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU44" | |
| type: "ReLU" | |
| bottom: "blob93" | |
| top: "blob93" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_net3_upsample_flow6to5" | |
| type: "Deconvolution" | |
| bottom: "blob92" | |
| top: "blob94" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat12" | |
| type: "Concat" | |
| bottom: "blob89" | |
| bottom: "blob93" | |
| bottom: "blob94" | |
| top: "blob95" | |
| } | |
| layer { | |
| name: "net3_predict_conv5" | |
| type: "Convolution" | |
| bottom: "blob95" | |
| top: "blob96" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_deconv4" | |
| type: "Deconvolution" | |
| bottom: "blob95" | |
| top: "blob97" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU45" | |
| type: "ReLU" | |
| bottom: "blob97" | |
| top: "blob97" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_net3_upsample_flow5to4" | |
| type: "Deconvolution" | |
| bottom: "blob96" | |
| top: "blob98" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat13" | |
| type: "Concat" | |
| bottom: "blob87" | |
| bottom: "blob97" | |
| bottom: "blob98" | |
| top: "blob99" | |
| } | |
| layer { | |
| name: "net3_predict_conv4" | |
| type: "Convolution" | |
| bottom: "blob99" | |
| top: "blob100" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_deconv3" | |
| type: "Deconvolution" | |
| bottom: "blob99" | |
| top: "blob101" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU46" | |
| type: "ReLU" | |
| bottom: "blob101" | |
| top: "blob101" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_net3_upsample_flow4to3" | |
| type: "Deconvolution" | |
| bottom: "blob100" | |
| top: "blob102" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat14" | |
| type: "Concat" | |
| bottom: "blob85" | |
| bottom: "blob101" | |
| bottom: "blob102" | |
| top: "blob103" | |
| } | |
| layer { | |
| name: "net3_predict_conv3" | |
| type: "Convolution" | |
| bottom: "blob103" | |
| top: "blob104" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_deconv2" | |
| type: "Deconvolution" | |
| bottom: "blob103" | |
| top: "blob105" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU47" | |
| type: "ReLU" | |
| bottom: "blob105" | |
| top: "blob105" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "net3_net3_upsample_flow3to2" | |
| type: "Deconvolution" | |
| bottom: "blob104" | |
| top: "blob106" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat15" | |
| type: "Concat" | |
| bottom: "blob83" | |
| bottom: "blob105" | |
| bottom: "blob106" | |
| top: "blob107" | |
| } | |
| layer { | |
| name: "net3_predict_conv2" | |
| type: "Convolution" | |
| bottom: "blob107" | |
| top: "blob108" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Eltwise9" | |
| type: "Eltwise" | |
| bottom: "blob108" | |
| top: "blob109" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 20.0 | |
| } | |
| } | |
| layer { | |
| name: "Concat16" | |
| type: "Concat" | |
| bottom: "img0_nomean_resize" | |
| bottom: "img1_nomean_resize" | |
| top: "blob110" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv0" | |
| type: "Convolution" | |
| bottom: "blob110" | |
| top: "blob111" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU48" | |
| type: "ReLU" | |
| bottom: "blob111" | |
| top: "blob111" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv1" | |
| type: "Convolution" | |
| bottom: "blob111" | |
| top: "blob112" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU49" | |
| type: "ReLU" | |
| bottom: "blob112" | |
| top: "blob112" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv1_1" | |
| type: "Convolution" | |
| bottom: "blob112" | |
| top: "blob113" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU50" | |
| type: "ReLU" | |
| bottom: "blob113" | |
| top: "blob113" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv2" | |
| type: "Convolution" | |
| bottom: "blob113" | |
| top: "blob114" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU51" | |
| type: "ReLU" | |
| bottom: "blob114" | |
| top: "blob114" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv2_1" | |
| type: "Convolution" | |
| bottom: "blob114" | |
| top: "blob115" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU52" | |
| type: "ReLU" | |
| bottom: "blob115" | |
| top: "blob115" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv3" | |
| type: "Convolution" | |
| bottom: "blob115" | |
| top: "blob116" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU53" | |
| type: "ReLU" | |
| bottom: "blob116" | |
| top: "blob116" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv3_1" | |
| type: "Convolution" | |
| bottom: "blob116" | |
| top: "blob117" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU54" | |
| type: "ReLU" | |
| bottom: "blob117" | |
| top: "blob117" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv4" | |
| type: "Convolution" | |
| bottom: "blob117" | |
| top: "blob118" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU55" | |
| type: "ReLU" | |
| bottom: "blob118" | |
| top: "blob118" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv4_1" | |
| type: "Convolution" | |
| bottom: "blob118" | |
| top: "blob119" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU56" | |
| type: "ReLU" | |
| bottom: "blob119" | |
| top: "blob119" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv5" | |
| type: "Convolution" | |
| bottom: "blob119" | |
| top: "blob120" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU57" | |
| type: "ReLU" | |
| bottom: "blob120" | |
| top: "blob120" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv5_1" | |
| type: "Convolution" | |
| bottom: "blob120" | |
| top: "blob121" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU58" | |
| type: "ReLU" | |
| bottom: "blob121" | |
| top: "blob121" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv6" | |
| type: "Convolution" | |
| bottom: "blob121" | |
| top: "blob122" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU59" | |
| type: "ReLU" | |
| bottom: "blob122" | |
| top: "blob122" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_conv6_1" | |
| type: "Convolution" | |
| bottom: "blob122" | |
| top: "blob123" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU60" | |
| type: "ReLU" | |
| bottom: "blob123" | |
| top: "blob123" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_Convolution1" | |
| type: "Convolution" | |
| bottom: "blob123" | |
| top: "blob124" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_deconv5" | |
| type: "Deconvolution" | |
| bottom: "blob123" | |
| top: "blob125" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU61" | |
| type: "ReLU" | |
| bottom: "blob125" | |
| top: "blob125" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_upsample_flow6to5" | |
| type: "Deconvolution" | |
| bottom: "blob124" | |
| top: "blob126" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat17" | |
| type: "Concat" | |
| bottom: "blob121" | |
| bottom: "blob125" | |
| bottom: "blob126" | |
| top: "blob127" | |
| } | |
| layer { | |
| name: "netsd_interconv5" | |
| type: "Convolution" | |
| bottom: "blob127" | |
| top: "blob128" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_Convolution2" | |
| type: "Convolution" | |
| bottom: "blob128" | |
| top: "blob129" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_deconv4" | |
| type: "Deconvolution" | |
| bottom: "blob127" | |
| top: "blob130" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU62" | |
| type: "ReLU" | |
| bottom: "blob130" | |
| top: "blob130" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_upsample_flow5to4" | |
| type: "Deconvolution" | |
| bottom: "blob129" | |
| top: "blob131" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat18" | |
| type: "Concat" | |
| bottom: "blob119" | |
| bottom: "blob130" | |
| bottom: "blob131" | |
| top: "blob132" | |
| } | |
| layer { | |
| name: "netsd_interconv4" | |
| type: "Convolution" | |
| bottom: "blob132" | |
| top: "blob133" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_Convolution3" | |
| type: "Convolution" | |
| bottom: "blob133" | |
| top: "blob134" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_deconv3" | |
| type: "Deconvolution" | |
| bottom: "blob132" | |
| top: "blob135" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU63" | |
| type: "ReLU" | |
| bottom: "blob135" | |
| top: "blob135" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_upsample_flow4to3" | |
| type: "Deconvolution" | |
| bottom: "blob134" | |
| top: "blob136" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat19" | |
| type: "Concat" | |
| bottom: "blob117" | |
| bottom: "blob135" | |
| bottom: "blob136" | |
| top: "blob137" | |
| } | |
| layer { | |
| name: "netsd_interconv3" | |
| type: "Convolution" | |
| bottom: "blob137" | |
| top: "blob138" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_Convolution4" | |
| type: "Convolution" | |
| bottom: "blob138" | |
| top: "blob139" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_deconv2" | |
| type: "Deconvolution" | |
| bottom: "blob137" | |
| top: "blob140" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU64" | |
| type: "ReLU" | |
| bottom: "blob140" | |
| top: "blob140" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_upsample_flow3to2" | |
| type: "Deconvolution" | |
| bottom: "blob139" | |
| top: "blob141" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat20" | |
| type: "Concat" | |
| bottom: "blob115" | |
| bottom: "blob140" | |
| bottom: "blob141" | |
| top: "blob142" | |
| } | |
| layer { | |
| name: "netsd_interconv2" | |
| type: "Convolution" | |
| bottom: "blob142" | |
| top: "blob143" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "netsd_Convolution5" | |
| type: "Convolution" | |
| bottom: "blob143" | |
| top: "blob144" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Eltwise10" | |
| type: "Eltwise" | |
| bottom: "blob144" | |
| top: "blob145" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.05 | |
| } | |
| } | |
| layer { | |
| name: "Resample3" | |
| type: "Resample" | |
| bottom: "blob145" | |
| bottom: "img0_nomean_resize" | |
| top: "blob146" | |
| resample_param { | |
| type: NEAREST | |
| antialias: false | |
| factor: 1.0 | |
| } | |
| } | |
| layer { | |
| name: "Resample4" | |
| type: "Resample" | |
| bottom: "blob109" | |
| bottom: "img0_nomean_resize" | |
| top: "blob147" | |
| resample_param { | |
| type: NEAREST | |
| antialias: false | |
| factor: 1.0 | |
| } | |
| } | |
| layer { | |
| name: "ChannelNorm3" | |
| type: "ChannelNorm" | |
| bottom: "blob146" | |
| top: "blob148" | |
| } | |
| layer { | |
| name: "ChannelNorm4" | |
| type: "ChannelNorm" | |
| bottom: "blob147" | |
| top: "blob149" | |
| } | |
| layer { | |
| name: "FlowWarp3" | |
| type: "FlowWarp" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob146" | |
| top: "blob150" | |
| } | |
| layer { | |
| name: "Eltwise11" | |
| type: "Eltwise" | |
| bottom: "img0_nomean_resize" | |
| bottom: "blob150" | |
| top: "blob151" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1.0 | |
| coeff: -1.0 | |
| } | |
| } | |
| layer { | |
| name: "ChannelNorm5" | |
| type: "ChannelNorm" | |
| bottom: "blob151" | |
| top: "blob152" | |
| } | |
| layer { | |
| name: "FlowWarp4" | |
| type: "FlowWarp" | |
| bottom: "img1_nomean_resize" | |
| bottom: "blob147" | |
| top: "blob153" | |
| } | |
| layer { | |
| name: "Eltwise12" | |
| type: "Eltwise" | |
| bottom: "img0_nomean_resize" | |
| bottom: "blob153" | |
| top: "blob154" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1.0 | |
| coeff: -1.0 | |
| } | |
| } | |
| layer { | |
| name: "ChannelNorm6" | |
| type: "ChannelNorm" | |
| bottom: "blob154" | |
| top: "blob155" | |
| } | |
| layer { | |
| name: "Concat21" | |
| type: "Concat" | |
| bottom: "img0_nomean_resize" | |
| bottom: "blob146" | |
| bottom: "blob147" | |
| bottom: "blob148" | |
| bottom: "blob149" | |
| bottom: "blob152" | |
| bottom: "blob155" | |
| top: "blob156" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "fuse_conv0" | |
| type: "Convolution" | |
| bottom: "blob156" | |
| top: "blob157" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU65" | |
| type: "ReLU" | |
| bottom: "blob157" | |
| top: "blob157" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_conv1" | |
| type: "Convolution" | |
| bottom: "blob157" | |
| top: "blob158" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU66" | |
| type: "ReLU" | |
| bottom: "blob158" | |
| top: "blob158" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_conv1_1" | |
| type: "Convolution" | |
| bottom: "blob158" | |
| top: "blob159" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU67" | |
| type: "ReLU" | |
| bottom: "blob159" | |
| top: "blob159" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_conv2" | |
| type: "Convolution" | |
| bottom: "blob159" | |
| top: "blob160" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU68" | |
| type: "ReLU" | |
| bottom: "blob160" | |
| top: "blob160" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_conv2_1" | |
| type: "Convolution" | |
| bottom: "blob160" | |
| top: "blob161" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU69" | |
| type: "ReLU" | |
| bottom: "blob161" | |
| top: "blob161" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse__Convolution5" | |
| type: "Convolution" | |
| bottom: "blob161" | |
| top: "blob162" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_deconv1" | |
| type: "Deconvolution" | |
| bottom: "blob161" | |
| top: "blob163" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU70" | |
| type: "ReLU" | |
| bottom: "blob163" | |
| top: "blob163" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_upsample_flow2to1" | |
| type: "Deconvolution" | |
| bottom: "blob162" | |
| top: "blob164" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat22" | |
| type: "Concat" | |
| bottom: "blob159" | |
| bottom: "blob163" | |
| bottom: "blob164" | |
| top: "blob165" | |
| } | |
| layer { | |
| name: "fuse_interconv1" | |
| type: "Convolution" | |
| bottom: "blob165" | |
| top: "blob166" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse__Convolution6" | |
| type: "Convolution" | |
| bottom: "blob166" | |
| top: "blob167" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_deconv0" | |
| type: "Deconvolution" | |
| bottom: "blob165" | |
| top: "blob168" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU71" | |
| type: "ReLU" | |
| bottom: "blob168" | |
| top: "blob168" | |
| relu_param { | |
| negative_slope: 0.1 | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse_upsample_flow1to0" | |
| type: "Deconvolution" | |
| bottom: "blob167" | |
| top: "blob169" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat23" | |
| type: "Concat" | |
| bottom: "blob157" | |
| bottom: "blob168" | |
| bottom: "blob169" | |
| top: "blob170" | |
| } | |
| layer { | |
| name: "fuse_interconv0" | |
| type: "Convolution" | |
| bottom: "blob170" | |
| top: "blob171" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "fuse__Convolution7" | |
| type: "Convolution" | |
| bottom: "blob171" | |
| top: "blob172" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 2 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Resample5" | |
| type: "Resample" | |
| bottom: "blob172" | |
| top: "predict_flow_resize" | |
| resample_param { | |
| width: 1024 | |
| height: 720 | |
| type: LINEAR | |
| antialias: true | |
| } | |
| } | |
| layer { | |
| name: "scale_conv1" | |
| type: "Convolution" | |
| bottom: "predict_flow_resize" | |
| top: "predict_flow_final" | |
| convolution_param { | |
| num_output: 2 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "diagonal" | |
| diag_val: 1 | |
| diag_val: 0.9375 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
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