Interpretable multi-modal image registration network based on disentangled convolutional sparse coding
Multi-modal image registration aims to spatially align two images from different modalities to
make their feature points match with each other. Captured by different sensors, the images …
make their feature points match with each other. Captured by different sensors, the images …
Learning guided convolutional network for depth completion
Dense depth perception is critical for autonomous driving and other robotics applications.
However, modern LiDAR sensors only provide sparse depth measurement. It is thus …
However, modern LiDAR sensors only provide sparse depth measurement. It is thus …
Fast end-to-end trainable guided filter
Image processing and pixel-wise dense prediction have been advanced by harnessing the
capabilities of deep learning. One central issue of deep learning is the limited capacity to …
capabilities of deep learning. One central issue of deep learning is the limited capacity to …
Deep convolutional neural network for multi-modal image restoration and fusion
X Deng, PL Dragotti - IEEE transactions on pattern analysis …, 2020 - ieeexplore.ieee.org
In this paper, we propose a novel deep convolutional neural network to solve the general
multi-modal image restoration (MIR) and multi-modal image fusion (MIF) problems. Different …
multi-modal image restoration (MIR) and multi-modal image fusion (MIF) problems. Different …
Deep joint image filtering
Joint image filters can leverage the guidance image as a prior and transfer the structural
details from the guidance image to the target image for suppressing noise or enhancing …
details from the guidance image to the target image for suppressing noise or enhancing …
Joint image filtering with deep convolutional networks
Joint image filters leverage the guidance image as a prior and transfer the structural details
from the guidance image to the target image for suppressing noise or enhancing spatial …
from the guidance image to the target image for suppressing noise or enhancing spatial …
Robust guided image filtering using nonconvex potentials
Filtering images using a guidance signal, a process called guided or joint image filtering,
has been used in various tasks in computer vision and computational photography …
has been used in various tasks in computer vision and computational photography …
Darkvisionnet: Low-light imaging via rgb-nir fusion with deep inconsistency prior
RGB-NIR fusion is a promising method for low-light imaging. However, high-intensity noise
in low-light images amplifies the effect of structure inconsistency between RGB-NIR images …
in low-light images amplifies the effect of structure inconsistency between RGB-NIR images …
Mutual-structure for joint filtering
Previous joint/guided filters directly transfer the structural information in the reference image
to the target one. In this paper, we first analyze its major drawback--that is, there may be …
to the target one. In this paper, we first analyze its major drawback--that is, there may be …
Deformable kernel networks for joint image filtering
Joint image filters are used to transfer structural details from a guidance picture used as a
prior to a target image, in tasks such as enhancing spatial resolution and suppressing noise …
prior to a target image, in tasks such as enhancing spatial resolution and suppressing noise …