Attention-guided network for ghost-free high dynamic range imaging
Ghosting artifacts caused by moving objects or misalignments is a key challenge in high
dynamic range (HDR) imaging for dynamic scenes. Previous methods first register the input …
dynamic range (HDR) imaging for dynamic scenes. Previous methods first register the input …
Deep HDR imaging via a non-local network
One of the most challenging problems in reconstructing a high dynamic range (HDR) image
from multiple low dynamic range (LDR) inputs is the ghosting artifacts caused by the object …
from multiple low dynamic range (LDR) inputs is the ghosting artifacts caused by the object …
Towards 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 …
A unified HDR imaging method with pixel and patch level
Q Yan, W Chen, S Zhang, Y Zhu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Mapping Low Dynamic Range (LDR) images with different exposures to High
Dynamic Range (HDR) remains nontrivial and challenging on dynamic scenes due to …
Dynamic Range (HDR) remains nontrivial and challenging on dynamic scenes due to …
Two-stream convolutional networks for blind image quality assessment
Traditional image quality assessment (IQA) methods do not perform robustly due to the
shallow hand-designed features. It has been demonstrated that deep neural network can …
shallow hand-designed features. It has been demonstrated that deep neural network can …
Smae: Few-shot learning for hdr deghosting with saturation-aware masked autoencoders
Generating a high-quality High Dynamic Range (HDR) image from dynamic scenes has
recently been extensively studied by exploiting Deep Neural Networks (DNNs). Most DNNs …
recently been extensively studied by exploiting Deep Neural Networks (DNNs). Most DNNs …
Dual-attention-guided network for ghost-free high dynamic range imaging
Ghosting artifacts caused by moving objects and misalignments are a key challenge in
constructing high dynamic range (HDR) images. Current methods first register the input low …
constructing high dynamic range (HDR) images. Current methods first register the input low …
Generating content for hdr deghosting from frequency view
Abstract Recovering ghost-free High Dynamic Range (HDR) images from multiple Low
Dynamic Range (LDR) images becomes challenging when the LDR images exhibit …
Dynamic Range (LDR) images becomes challenging when the LDR images exhibit …
Multi-scale dense networks for deep high dynamic range imaging
Generating a high dynamic range (HDR) image from a set of sequential exposures is a
challenging task for dynamic scenes. The most common approaches are aligning the input …
challenging task for dynamic scenes. The most common approaches are aligning the input …
Selective transhdr: Transformer-based selective hdr imaging using ghost region mask
The primary issue in high dynamic range (HDR) imaging is the removal of ghost artifacts
afforded when merging multi-exposure low dynamic range images. In the weakly misaligned …
afforded when merging multi-exposure low dynamic range images. In the weakly misaligned …