i want to use 3d convolution on 2d input images, on any datasets , just want to learn more from codes, its easy for me.
More precisely, i want to apply a 3d kernel on inputs(h,w,c),l mean, each channel need to be convolved with kernel not all with same kernel. i.e : my datasets has 100x100x5 , wanna apply kernel size of 5 channels , not the sum of these 5 kernels as the 2D conv really is.just to preserve the same depth of the image during the convolution.
I hope that makes sense.