1 code implementation • 19 Jul 2022 • Xiaoyu Dong, Naoto Yokoya, Longguang Wang, Tatsumi Uezato
Self-supervised cross-modal super-resolution (SR) can overcome the difficulty of acquiring paired training data, but is challenging because only low-resolution (LR) source and high-resolution (HR) guide images from different modalities are available.
no code implementations • 23 Jul 2020 • Tatsumi Uezato, Naoto Yokoya, wei he
Although many spectral unmixing models have been developed to address spectral variability caused by variable incident illuminations, the mechanism of the spectral variability is still unclear.
1 code implementation • ECCV 2020 • Tatsumi Uezato, Danfeng Hong, Naoto Yokoya, wei he
The proposed network is composed of an encoder-decoder network that exploits multi-scale features of a guidance image and a deep decoder network that generates an output image.
no code implementations • 30 Apr 2018 • Tatsumi Uezato, Mathieu Fauvel, Nicolas Dobigeon
The proposed method is designed to promote sparsity on the selection of both spectra and classes within each pixel.