Generative adversarial networks via a composite annealing of noise and diffusion-Reference-Cited by-同舟云学术

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Generative adversarial networks via a composite annealing of noise and diffusion

Published:2024-02 Issue: Volume:146 Page:110034
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Nakamura Kensuke^ORCID,Korman Simon,Hong Byung-Woo^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference70 articles.

1. Generative adversarial nets;Goodfellow,2014

2. Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models;Bond-Taylor;IEEE Trans. Pattern Anal. Mach. Intell.,2021

3. L.D. Tran, S.M. Nguyen, M. Arai, GAN-based noise model for denoising real images, in: Proceedings of the Asian Conference on Computer Vision, 2020.

4. AI-GAN: Asynchronous interactive generative adversarial network for single image rain removal;Jin;Pattern Recognit.,2020

5. De-gan: A conditional generative adversarial network for document enhancement;Souibgui;IEEE Trans. Pattern Anal. Mach. Intell.,2020

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