114 citations · 166 across the 4 of their papers we have counts for
4 papers
PolMERLIN: Self-Supervised Polarimetric Complex SAR Image Despeckling with Masked Networks
Shunya Kato, Masaki Saito, Katsuhiko Ishiguro +1
Despeckling is a crucial noise reduction task in improving the quality of synthetic aperture radar (SAR) images. Directly obtaining noise-free SAR images is a challenging task that…
Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN
Masaki Saito, Shunta Saito, Masanori Koyama +1
Training of Generative Adversarial Network (GAN) on a video dataset is a challenge because of the sheer size of the dataset and the complexity of each observation. In general, the…
ChainerCV: a Library for Deep Learning in Computer Vision
Yusuke Niitani, Toru Ogawa, Shunta Saito +1
Despite significant progress of deep learning in the field of computer vision, there has not been a software library that covers these methods in a unifying manner. We introduce Ch…
Temporal Generative Adversarial Nets with Singular Value Clipping
Masaki Saito, Eiichi Matsumoto, Shunta Saito
In this paper, we propose a generative model, Temporal Generative Adversarial Nets (TGAN), which can learn a semantic representation of unlabeled videos, and is capable of generati…