arXiv Open Access 2022

Multi-Modality Image Super-Resolution using Generative Adversarial Networks

Aref Abedjooy Mehran Ebrahimi

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Abstrak

Over the past few years deep learning-based techniques such as Generative Adversarial Networks (GANs) have significantly improved solutions to image super-resolution and image-to-image translation problems. In this paper, we propose a solution to the joint problem of image super-resolution and multi-modality image-to-image translation. The problem can be stated as the recovery of a high-resolution image in a modality, given a low-resolution observation of the same image in an alternative modality. Our paper offers two models to address this problem and will be evaluated on the recovery of high-resolution day images given low-resolution night images of the same scene. Promising qualitative and quantitative results will be presented for each model.

Topik & Kata Kunci

eess.IV cs.CV cs.LG

Penulis (2)

Aref Abedjooy

Mehran Ebrahimi

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APA MLA BibTeX

Abedjooy, A., Ebrahimi, M. (2022). Multi-Modality Image Super-Resolution using Generative Adversarial Networks. https://arxiv.org/abs/2206.09193

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓