GANs use transposed convolutions to generate images. I haven’t seen anyone use a true deconvolution operation in deep learning. Not even sure it’s possible to invert the result of a convolutional layer, because it’s lossy.
"Transposed convolution" was called "deconvolution" for a short period of time. The authors apparently weren't aware that "deconvolution" has meant "the inverse problem of recovering a convolved signal" since at least the 70s.