Hi @kembo,
Thank you for your answer.
I’m not learning on my images. I just use ResNet-152 as a feature extractor.
So the idea, is to take each superpixel (a set of pixels) of a given image as a whole image and 0-pad it to get image into -224,224,3).
So for an image  M with K superpixels, l build K images of dimension (224,224,3), their spatial dimensions are different but they are 0-padded. These K images are fed to ResNet-152 to extract features.  So for image M l get   K x 2048 feature vector.
However, l’m wondering if there is any negative impact (poor feature representation) on Resnet152 due to the fact of padding an image such that one superpixel is about 8% information on the image and the remaining 92% are  0 .
Thank you for your answer