  We address the problem of decomposing an image into albedo and shading. We
propose the Fast Fourier Intrinsic Network, FFI-Net in short, that operates in
the spectral domain, splitting the input into several spectral bands. Weights
in FFI-Net are optimized in the spectral domain, allowing faster convergence to
a lower error. FFI-Net is lightweight and does not need auxiliary networks for
training. The network is trained end-to-end with a novel spectral loss which
measures the global distance between the network prediction and corresponding
ground truth. FFI-Net achieves state-of-the-art performance on MPI-Sintel, MIT
Intrinsic, and IIW datasets.
