NTIRE 2023 challenge on image denoising: Methods and results
This paper reviews the NTIRE 2023 challenge on image denoising (sigma= 50) with a focus
on the proposed solutions and results. The aim is to obtain a network design capable to …
on the proposed solutions and results. The aim is to obtain a network design capable to …
Ntire 2019 challenge on real image denoising: Methods and results
This paper reviews the NTIRE 2019 challenge on real image denoising with focus on the
proposed methods and their results. The challenge has two tracks for quantitatively …
proposed methods and their results. The challenge has two tracks for quantitatively …
R2rnet: Low-light image enhancement via real-low to real-normal network
J Hai, Z Xuan, R Yang, Y Hao, F Zou, F Lin… - Journal of Visual …, 2023 - Elsevier
Images captured in weak illumination conditions could seriously degrade the image quality.
Solving a series of degradation of low-light images can effectively improve the visual quality …
Solving a series of degradation of low-light images can effectively improve the visual quality …
Dual adversarial network: Toward real-world noise removal and noise generation
Real-world image noise removal is a long-standing yet very challenging task in computer
vision. The success of deep neural network in denoising stimulates the research of noise …
vision. The success of deep neural network in denoising stimulates the research of noise …
Image processing using multi-code gan prior
Despite the success of Generative Adversarial Networks (GANs) in image synthesis,
applying trained GAN models to real image processing remains challenging. Previous …
applying trained GAN models to real image processing remains challenging. Previous …
Invertible denoising network: A light solution for real noise removal
Invertible networks have various benefits for image denoising since they are lightweight,
information-lossless, and memory-saving during back-propagation. However, applying …
information-lossless, and memory-saving during back-propagation. However, applying …
Dual-gan: Joint bvp and noise modeling for remote physiological measurement
Remote photoplethysmography (rPPG) based physiological measurement has great
application values in health monitoring, emotion analysis, etc. Existing methods mainly focus …
application values in health monitoring, emotion analysis, etc. Existing methods mainly focus …
Tomato leaf disease identification by restructured deep residual dense network
C Zhou, S Zhou, J **ng, J Song - IEEE Access, 2021 - ieeexplore.ieee.org
As COVID-19 spread worldwide, many major grain-producing countries have adopted
measures to restrict their grain exports; food security has aroused great concern from …
measures to restrict their grain exports; food security has aroused great concern from …
A survey of deep learning approaches to image restoration
In this paper, we present an extensive review on deep learning methods for image
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …
Fast bi-layer neural synthesis of one-shot realistic head avatars
We propose a neural rendering-based system that creates head avatars from a single
photograph. Our approach models a person's appearance by decomposing it into two …
photograph. Our approach models a person's appearance by decomposing it into two …