layer_correlation_cost | R Documentation |
Correlation Cost Layer.
layer_correlation_cost( object, kernel_size, max_displacement, stride_1, stride_2, pad, data_format, ... )
object |
Model or layer object |
kernel_size |
An integer specifying the height and width of the patch used to compute the per-patch costs. |
max_displacement |
An integer specifying the maximum search radius for each position. |
stride_1 |
An integer specifying the stride length in the input. |
stride_2 |
An integer specifying the stride length in the patch. |
pad |
An integer specifying the paddings in height and width. |
data_format |
Specifies the data format. Possible values are: "channels_last" float [batch, height, width, channels] "channels_first" float [batch, channels, height, width] Defaults to "channels_last". |
... |
additional parameters to pass |
This layer implements the correlation operation from FlowNet Learning Optical Flow with Convolutional Networks (Fischer et al.): https://arxiv.org/abs/1504.06
A tensor
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