Fast fourier intrinsic network
Qian, Yanlin; Shi, Miaojing; Kämäräinen, Joni-Kristian; Matas, Jiri (2021-01)
Qian, Yanlin
Shi, Miaojing
Kämäräinen, Joni-Kristian
Matas, Jiri
01 / 2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202307277314
https://urn.fi/URN:NBN:fi:tuni-202307277314
Kuvaus
Peer reviewed
Tiivistelmä
<p>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.</p>
Kokoelmat
- TUNICRIS-julkaisut [20143]