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20162024
most citedTrain Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN

114 citations · 166 across the 4 of their papers we have counts for

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cs.CV2024

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…