layer_correlation_cost {tfaddons} | R Documentation |
Correlation Cost Layer.
Description
Correlation Cost Layer.
Usage
layer_correlation_cost(
object,
kernel_size,
max_displacement,
stride_1,
stride_2,
pad,
data_format,
...
)
Arguments
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 |
Details
This layer implements the correlation operation from FlowNet Learning Optical Flow with Convolutional Networks (Fischer et al.): https://arxiv.org/abs/1504.06
Value
A tensor
[Package tfaddons version 0.10.0 Index]