NTIRE 2024 Challenge on Bracketing Image Restoration and Enhancement: Datasets Methods and Results
Low-light photography presents significant challenges. Multi-image processing methods
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
Deep learning for hdr imaging: State-of-the-art and future trends
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 …
Generative diffusion prior for unified image restoration and enhancement
Existing image restoration methods mostly leverage the posterior distribution of natural
images. However, they often assume known degradation and also require supervised …
images. However, they often assume known degradation and also require supervised …
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 …
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 …
HDR video reconstruction: A coarse-to-fine network and a real-world benchmark dataset
High dynamic range (HDR) video reconstruction from sequences captured with alternating
exposures is a very challenging problem. Existing methods often align low dynamic range …
exposures is a very challenging problem. Existing methods often align low dynamic range …
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 …
Multi-bracket high dynamic range imaging with event cameras
N Messikommer, S Georgoulis… - Proceedings of the …, 2022 - openaccess.thecvf.com
Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic
range (LDR) images captured at different exposure times. While these methods work well in …
range (LDR) images captured at different exposure times. While these methods work well in …
Improving dynamic hdr imaging with fusion transformer
Abstract Reconstructing a High Dynamic Range (HDR) image from several Low Dynamic
Range (LDR) images with different exposures is a challenging task, especially in the …
Range (LDR) images with different exposures is a challenging task, especially in the …