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CRL
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| name: "crl" | |
| layer { | |
| name: "Image1" | |
| type: "Input" | |
| top: "img0" | |
| input_param { shape: { dim: 1 dim: 3 dim: 320 dim: 1792 } } | |
| } | |
| layer { | |
| name: "Image2" | |
| type: "Input" | |
| top: "img1" | |
| input_param { shape: { dim: 1 dim: 3 dim: 320 dim: 1792 } } | |
| } | |
| layer { | |
| name: "Eltwise2" | |
| type: "Eltwise" | |
| bottom: "img1" | |
| top: "img1s" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.00392156862745098 | |
| } | |
| } | |
| layer { | |
| name: "Eltwise1" | |
| type: "Eltwise" | |
| bottom: "img0" | |
| top: "img0s" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 0.00392156862745098 | |
| } | |
| } | |
| layer { | |
| name: "img0s_aug" | |
| type: "Eltwise" | |
| bottom: "img0s" | |
| top: "img0_nomean" | |
| } | |
| layer { | |
| name: "img1s_aug" | |
| type: "Eltwise" | |
| bottom: "img1s" | |
| top: "img1_nomean" | |
| } | |
| layer { | |
| name: "Resample1" | |
| type: "Resample" | |
| bottom: "img0_nomean" | |
| top: "img0_aug" | |
| } | |
| layer { | |
| name: "Resample2" | |
| type: "Resample" | |
| bottom: "img1_nomean" | |
| top: "img1_aug" | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "img0_aug" | |
| bottom: "img1_aug" | |
| top: "conv1a" | |
| top: "conv1b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU1" | |
| type: "ReLU" | |
| bottom: "conv1a" | |
| top: "conv1a" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "ReLU2" | |
| type: "ReLU" | |
| bottom: "conv1b" | |
| top: "conv1b" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv1a" | |
| bottom: "conv1b" | |
| top: "conv2a" | |
| top: "conv2b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU3" | |
| type: "ReLU" | |
| bottom: "conv2a" | |
| top: "conv2a" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "ReLU4" | |
| type: "ReLU" | |
| bottom: "conv2b" | |
| top: "conv2b" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "corr" | |
| type: "Correlation1D" | |
| bottom: "conv2a" | |
| bottom: "conv2b" | |
| top: "corr" | |
| } | |
| layer { | |
| name: "conv_redir" | |
| type: "Convolution" | |
| bottom: "conv2a" | |
| top: "conv_redir" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU5" | |
| type: "ReLU" | |
| bottom: "conv_redir" | |
| top: "conv_redir" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "Concat2" | |
| type: "Concat" | |
| bottom: "corr" | |
| bottom: "conv_redir" | |
| top: "blob20" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "blob20" | |
| top: "conv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU6" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU7" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU8" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU9" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU10" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Convolution" | |
| bottom: "conv5" | |
| top: "conv5_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU11" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU12" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv6_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 1 | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU13" | |
| type: "ReLU" | |
| bottom: "conv6_1" | |
| top: "conv6_1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU14" | |
| type: "ReLU" | |
| bottom: "deconv5" | |
| top: "deconv5" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat3" | |
| type: "Concat" | |
| bottom: "conv5_1" | |
| bottom: "deconv5" | |
| bottom: "upsampled_flow6_to_5" | |
| top: "blob34" | |
| } | |
| layer { | |
| name: "Convolution2" | |
| type: "Convolution" | |
| bottom: "blob34" | |
| top: "concat5" | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution3" | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU15" | |
| type: "ReLU" | |
| bottom: "deconv4" | |
| top: "deconv4" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat4" | |
| type: "Concat" | |
| bottom: "conv4_1" | |
| bottom: "deconv4" | |
| bottom: "upsampled_flow5_to_4" | |
| top: "blob41" | |
| } | |
| layer { | |
| name: "Convolution4" | |
| type: "Convolution" | |
| bottom: "blob41" | |
| top: "concat4" | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution5" | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU16" | |
| type: "ReLU" | |
| bottom: "deconv3" | |
| top: "deconv3" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat5" | |
| type: "Concat" | |
| bottom: "conv3_1" | |
| bottom: "deconv3" | |
| bottom: "upsampled_flow4_to_3" | |
| top: "blob48" | |
| } | |
| layer { | |
| name: "Convolution6" | |
| type: "Convolution" | |
| bottom: "blob48" | |
| top: "concat3" | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution7" | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU17" | |
| type: "ReLU" | |
| bottom: "deconv2" | |
| top: "deconv2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat6" | |
| type: "Concat" | |
| bottom: "conv2a" | |
| bottom: "deconv2" | |
| bottom: "upsampled_flow3_to_2" | |
| top: "blob55" | |
| } | |
| layer { | |
| name: "Convolution8" | |
| type: "Convolution" | |
| bottom: "blob55" | |
| top: "concat2" | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution9" | |
| 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: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "deconv1" | |
| type: "Deconvolution" | |
| bottom: "concat2" | |
| top: "deconv1" | |
| param { | |
| lr_mult: 0 | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU18" | |
| type: "ReLU" | |
| bottom: "deconv1" | |
| top: "deconv1" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow2to1" | |
| type: "Deconvolution" | |
| bottom: "predict_flow2" | |
| top: "upsampled_flow2_to_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat7" | |
| type: "Concat" | |
| bottom: "conv1a" | |
| bottom: "deconv1" | |
| bottom: "upsampled_flow2_to_1" | |
| top: "blob62" | |
| } | |
| layer { | |
| name: "Convolution10" | |
| type: "Convolution" | |
| bottom: "blob62" | |
| top: "concat1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution11" | |
| type: "Convolution" | |
| bottom: "concat1" | |
| top: "predict_flow1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "deconv0" | |
| type: "Deconvolution" | |
| bottom: "concat1" | |
| top: "deconv0" | |
| param { | |
| lr_mult: 0 | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "ReLU19" | |
| type: "ReLU" | |
| bottom: "deconv0" | |
| top: "deconv0" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow1to0" | |
| type: "Deconvolution" | |
| bottom: "predict_flow1" | |
| top: "upsampled_flow1_to_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Concat8" | |
| type: "Concat" | |
| bottom: "img0_aug" | |
| bottom: "deconv0" | |
| bottom: "upsampled_flow1_to_0" | |
| top: "blob72" | |
| } | |
| layer { | |
| name: "Convolution12" | |
| type: "Convolution" | |
| bottom: "blob72" | |
| top: "concat0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| 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 | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "Convolution13" | |
| type: "Convolution" | |
| bottom: "concat0" | |
| top: "predict_flow0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "NegReLU7" | |
| type: "NegReLU" | |
| bottom: "predict_flow0" | |
| top: "blob76" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } | |
| layer { | |
| name: "zero" | |
| type: "Input" | |
| top: "zero" | |
| input_param { shape: { dim: 1 dim: 1 dim: 320 dim: 1792} } | |
| } | |
| layer { | |
| name: "coord_canon" | |
| type: "Input" | |
| top: "coord_canon" | |
| input_param { shape: { dim: 1 dim: 2 dim: 320 dim: 1792} } | |
| } | |
| layer { | |
| name: "disp_dup" | |
| type: "Concat" | |
| bottom: "blob76" | |
| bottom: "zero" | |
| top: "disp_dup" | |
| } | |
| layer { | |
| name: "coord_map" | |
| type: "Eltwise" | |
| bottom: "disp_dup" | |
| bottom: "coord_canon" | |
| top: "coord_map" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "img0_syn" | |
| type: "Remap" | |
| bottom: "img1_aug" | |
| bottom: "coord_map" | |
| top: "img0_syn" | |
| } | |
| layer { | |
| name: "bright_err" | |
| type: "Eltwise" | |
| bottom: "img0_aug" | |
| bottom: "img0_syn" | |
| top: "bright_err" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: -1 | |
| } | |
| } | |
| layer { | |
| name: "feed" | |
| type: "Concat" | |
| bottom: "blob76" | |
| bottom: "img0_aug" | |
| bottom: "img1_aug" | |
| bottom: "img0_syn" | |
| bottom: "bright_err" | |
| top: "feed" | |
| propagate_down: false | |
| propagate_down: false | |
| propagate_down: false | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "conv2_s2" | |
| type: "Convolution" | |
| bottom: "feed" | |
| top: "conv2_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "ReLU2_s2" | |
| type: "ReLU" | |
| bottom: "conv2_s2" | |
| top: "conv2_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_s2" | |
| type: "Convolution" | |
| bottom: "conv2_s2" | |
| top: "conv3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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_s2" | |
| type: "ReLU" | |
| bottom: "conv3_s2" | |
| top: "conv3_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_s2" | |
| type: "Convolution" | |
| bottom: "conv3_s2" | |
| top: "conv3_1_s2" | |
| 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: "ReLU4_s2" | |
| type: "ReLU" | |
| bottom: "conv3_1_s2" | |
| top: "conv3_1_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_s2" | |
| type: "Convolution" | |
| bottom: "conv3_1_s2" | |
| top: "conv4_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU5_s2" | |
| type: "ReLU" | |
| bottom: "conv4_s2" | |
| top: "conv4_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_s2" | |
| type: "Convolution" | |
| bottom: "conv4_s2" | |
| top: "conv4_1_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU6_s2" | |
| type: "ReLU" | |
| bottom: "conv4_1_s2" | |
| top: "conv4_1_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_s2" | |
| type: "Convolution" | |
| bottom: "conv4_1_s2" | |
| top: "conv5_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU7_s2" | |
| type: "ReLU" | |
| bottom: "conv5_s2" | |
| top: "conv5_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1_s2" | |
| type: "Convolution" | |
| bottom: "conv5_s2" | |
| top: "conv5_1_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU8_s2" | |
| type: "ReLU" | |
| bottom: "conv5_1_s2" | |
| top: "conv5_1_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_s2" | |
| type: "Convolution" | |
| bottom: "conv5_1_s2" | |
| top: "conv6_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU9_s2" | |
| type: "ReLU" | |
| bottom: "conv6_s2" | |
| top: "conv6_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1_s2" | |
| type: "Convolution" | |
| bottom: "conv6_s2" | |
| top: "conv6_1_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU10_s2" | |
| type: "ReLU" | |
| bottom: "conv6_1_s2" | |
| top: "conv6_1_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "Convolution1_s2" | |
| type: "Convolution" | |
| bottom: "conv6_1_s2" | |
| top: "Convolution1_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "disp_init_16_s2" | |
| type: "Downsample" | |
| bottom: "blob76" | |
| bottom: "Convolution1_s2" | |
| top: "disp_init_16_s2" | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "disp_16_s2" | |
| type: "Eltwise" | |
| bottom: "Convolution1_s2" | |
| bottom: "disp_init_16_s2" | |
| top: "disp_16_s2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "predict_flow6_s2" | |
| type: "NegReLU" | |
| bottom: "disp_16_s2" | |
| top: "predict_flow6_s2" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } | |
| layer { | |
| name: "deconv5_s2" | |
| type: "Deconvolution" | |
| bottom: "conv6_1_s2" | |
| top: "deconv5_s2" | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU11_s2" | |
| type: "ReLU" | |
| bottom: "deconv5_s2" | |
| top: "deconv5_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow6to5_s2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow6_s2" | |
| top: "upsample_flow6to5_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat3_s2" | |
| type: "Concat" | |
| bottom: "conv5_1_s2" | |
| bottom: "deconv5_s2" | |
| bottom: "upsample_flow6to5_s2" | |
| top: "Concat3_s2" | |
| } | |
| layer { | |
| name: "Convolution2_s2" | |
| type: "Convolution" | |
| bottom: "Concat3_s2" | |
| top: "Convolution2_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "Convolution3_s2" | |
| type: "Convolution" | |
| bottom: "Convolution2_s2" | |
| top: "Convolution3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "disp_init_8_s2" | |
| type: "Downsample" | |
| bottom: "blob76" | |
| bottom: "Convolution3_s2" | |
| top: "disp_init_8_s2" | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "disp_8_s2" | |
| type: "Eltwise" | |
| bottom: "Convolution3_s2" | |
| bottom: "disp_init_8_s2" | |
| top: "disp_8_s2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "predict_flow5_s2" | |
| type: "NegReLU" | |
| bottom: "disp_8_s2" | |
| top: "predict_flow5_s2" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } | |
| layer { | |
| name: "deconv4_s2" | |
| type: "Deconvolution" | |
| bottom: "Convolution2_s2" | |
| top: "deconv4_s2" | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU12_s2" | |
| type: "ReLU" | |
| bottom: "deconv4_s2" | |
| top: "deconv4_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow5to4_s2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow5_s2" | |
| top: "upsample_flow5to4_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat4_s2" | |
| type: "Concat" | |
| bottom: "conv4_1_s2" | |
| bottom: "deconv4_s2" | |
| bottom: "upsample_flow5to4_s2" | |
| top: "Concat4_s2" | |
| } | |
| layer { | |
| name: "Convolution4_s2" | |
| type: "Convolution" | |
| bottom: "Concat4_s2" | |
| top: "Convolution4_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| 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: "Convolution5_s2" | |
| type: "Convolution" | |
| bottom: "Convolution4_s2" | |
| top: "Convolution5_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "disp_init_4_s2" | |
| type: "Downsample" | |
| bottom: "blob76" | |
| bottom: "Convolution5_s2" | |
| top: "disp_init_4_s2" | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "disp_4_s2" | |
| type: "Eltwise" | |
| bottom: "Convolution5_s2" | |
| bottom: "disp_init_4_s2" | |
| top: "disp_4_s2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "predict_flow4_s2" | |
| type: "NegReLU" | |
| bottom: "disp_4_s2" | |
| top: "predict_flow4_s2" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } | |
| layer { | |
| name: "deconv3_s2" | |
| type: "Deconvolution" | |
| bottom: "Convolution4_s2" | |
| top: "deconv3_s2" | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU13_s2" | |
| type: "ReLU" | |
| bottom: "deconv3_s2" | |
| top: "deconv3_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow4to3_s2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow4_s2" | |
| top: "upsample_flow4to3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat5_s2" | |
| type: "Concat" | |
| bottom: "conv3_1_s2" | |
| bottom: "deconv3_s2" | |
| bottom: "upsample_flow4to3_s2" | |
| top: "Concat5_s2" | |
| } | |
| layer { | |
| name: "Convolution6_s2" | |
| type: "Convolution" | |
| bottom: "Concat5_s2" | |
| top: "Convolution6_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| 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: "Convolution7_s2" | |
| type: "Convolution" | |
| bottom: "Convolution6_s2" | |
| top: "Convolution7_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "disp_init_2_s2" | |
| type: "Downsample" | |
| bottom: "blob76" | |
| bottom: "Convolution7_s2" | |
| top: "disp_init_2_s2" | |
| propagate_down: false | |
| propagate_down: false | |
| } | |
| layer { | |
| name: "disp_2_s2" | |
| type: "Eltwise" | |
| bottom: "Convolution7_s2" | |
| bottom: "disp_init_2_s2" | |
| top: "disp_2_s2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "predict_flow3_s2" | |
| type: "NegReLU" | |
| bottom: "disp_2_s2" | |
| top: "predict_flow3_s2" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } | |
| layer { | |
| name: "deconv2_s2" | |
| type: "Deconvolution" | |
| bottom: "Convolution6_s2" | |
| top: "deconv2_s2" | |
| param { | |
| lr_mult: 1 | |
| 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: "ReLU14_s2" | |
| type: "ReLU" | |
| bottom: "deconv2_s2" | |
| top: "deconv2_s2" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "upsample_flow3to2_s2" | |
| type: "Deconvolution" | |
| bottom: "predict_flow3_s2" | |
| top: "upsample_flow3to2_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "Concat6_s2" | |
| type: "Concat" | |
| bottom: "conv2_s2" | |
| bottom: "deconv2_s2" | |
| bottom: "upsample_flow3to2_s2" | |
| top: "Concat6_s2" | |
| } | |
| layer { | |
| name: "Convolution8_s2" | |
| type: "Convolution" | |
| bottom: "Concat6_s2" | |
| top: "Convolution8_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| engine: CUDNN | |
| } | |
| } | |
| layer { | |
| name: "disp_1_s2" | |
| type: "Eltwise" | |
| bottom: "Convolution8_s2" | |
| bottom: "blob76" | |
| top: "disp_1_s2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "predict_flow2_s2" | |
| type: "NegReLU" | |
| bottom: "disp_1_s2" | |
| top: "predict_flow2_s2" | |
| relu_param { | |
| negative_slope: 0 | |
| } | |
| } |
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