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Deep learning for hdr imaging: State-of-the-art and future trends
L Wang, KJ Yoon - IEEE transactions on pattern analysis and …, 2021 - ieeexplore.ieee.org
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range
of exposures, which is important in image processing, computer graphics, and computer …
of exposures, which is important in image processing, computer graphics, and computer …
SUNet: Swin transformer UNet for image denoising
Image restoration is a challenging ill-posed problem which also has been a long-standing
issue. In the past few years, the convolution neural networks (CNNs) almost dominated the …
issue. In the past few years, the convolution neural networks (CNNs) almost dominated the …
Toward high-quality HDR deghosting with conditional diffusion models
High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range
(LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the …
(LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the …
Uncertainty estimation in HDR imaging with Bayesian neural networks
The goal of high dynamic range (HDR) imaging is to estimate potential high-quality images
from multi-exposed low dynamic range (LDR) inputs. Intuitively, there exist various possible …
from multi-exposed low dynamic range (LDR) inputs. Intuitively, there exist various possible …
AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system
The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
Ghost-free high dynamic range imaging with context-aware transformer
High dynamic range (HDR) deghosting algorithms aim to generate ghost-free HDR images
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
with realistic details. Restricted by the locality of the receptive field, existing CNN-based …
Hdr-gan: Hdr image reconstruction from multi-exposed ldr images with large motions
Y Niu, J Wu, W Liu, W Guo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Synthesizing high dynamic range (HDR) images from multiple low-dynamic range (LDR)
exposures in dynamic scenes is challenging. There are two major problems caused by the …
exposures in dynamic scenes is challenging. There are two major problems caused by the …
3D medical image segmentation using parallel transformers
Most recent 3D medical image segmentation methods adopt convolutional neural networks
(CNNs) that rely on deep feature representation and achieve adequate performance …
(CNNs) that rely on deep feature representation and achieve adequate performance …