Ntire 2020 challenge on real-world image super-resolution: Methods and results
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on
the participating methods and final results. The challenge addresses the real world setting …
the participating methods and final results. The challenge addresses the real world setting …
Ntire 2020 challenge on spectral reconstruction from an rgb image
This paper reviews the second challenge on spectral reconstruction from RGB images, ie,
the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image …
the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image …
Wavelet-based dual-branch network for image demoiréing
When smartphone cameras are used to take photos of digital screens, usually moiré
patterns result, severely degrading photo quality. In this paper, we design a wavelet-based …
patterns result, severely degrading photo quality. In this paper, we design a wavelet-based …
Ntire 2020 challenge on nonhomogeneous dehazing
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images
(restoration of rich details in hazy image). We focus on the proposed solutions and their …
(restoration of rich details in hazy image). We focus on the proposed solutions and their …
Ntire 2020 challenge on real image denoising: Dataset, methods and results
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the
newly introduced dataset, the proposed methods and their results. The challenge is a new …
newly introduced dataset, the proposed methods and their results. The challenge is a new …
Towards domain invariant single image dehazing
Presence of haze in images obscures underlying information, which is undesirable in
applications requiring accurate environment information. To recover such an image, a …
applications requiring accurate environment information. To recover such an image, a …
ClarifyNet: A high-pass and low-pass filtering based CNN for single image dehazing
Dehazing refers to removing the haze and restoring the details from hazy images. In this
paper, we propose ClarifyNet, a novel, end-to-end trainable, convolutional neural network …
paper, we propose ClarifyNet, a novel, end-to-end trainable, convolutional neural network …
Ntire 2020 challenge on perceptual extreme super-resolution: Methods and results
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with
focus on proposed solutions and results. The challenge task was to super-resolve an input …
focus on proposed solutions and results. The challenge task was to super-resolve an input …
Coarse-to-fine disentangling demoiréing framework for recaptured screen images
Removing the undesired moiré patterns from images capturing the contents displayed on
screens is of increasing research interest, as the need for recording and sharing the instant …
screens is of increasing research interest, as the need for recording and sharing the instant …
Unsupervised descriptor selection based meta-learning networks for few-shot classification
Z Hu, Z Li, X Wang, S Zheng - Pattern Recognition, 2022 - Elsevier
Meta-learning aims to train a classifier on collections of tasks, such that it can recognize new
classes given few samples from each. However, current approaches encounter overfitting …
classes given few samples from each. However, current approaches encounter overfitting …