Fast Fourier Intrinsic Network

• URL: http://arxiv.org/abs/2011.04612v1
• Date: Mon, 9 Nov 2020 18:14:39 GMT
• Title: Fast Fourier Intrinsic Network
• Authors: Yanlin Qian and Miaojing Shi and Joni-Kristian K\"am\"ar\"ainen and Jiri Matas
• Abstract summary: We propose the Fast Fourier Intrinsic Network, FFI-Net, that operates in the spectral domain. Weights in FFI-Net are optimized in the spectral domain, allowing faster convergence to a lower error. It achieves state-of-the-art performance on MPI-Sintel, MIT Intrinsic, and IIW datasets.
• Score: 41.95712986029093
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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