I have a vector which consists of a concatenation the features of a video sequence across 7 frames.
I would like to apply 1D convolution to this vector such that only a part of a frame is processed.
Say a feature vector for one frame has the lenght 10
-> my input feature vector would be of length 7 x 10 = 70
Now I want two convolutions to work on different parts of that vector
-> conv1 should treat the features 1:5
-> conv2 should treat 6:10
-> stride for both would be 10 -> so the convolution filters apply to the same features only in different frames
Basically I would need to specify an offset for the second conv filter. Is that possible?
On the Caffe website they speak only about a zero padding, but for an offset I would need a negative padding.
Is something like this possible?
layer {
name: "conv_layer"
type: "Convolution"
bottom: "data"
top: "conv_layer"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 90
kernel_h: 1
kernel_w: 5
pad_h: 0
pad_w: -5
stride: 10
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}