Learning multiple adverse weather removal via two-stage knowledge learning and multi-contrastive regularization: Toward a unified model
In this paper, an ill-posed problem of multiple adverse weather removal is investigated. Our
goal is to train a model with a'unified'architecture and only one set of pretrained weights that …
goal is to train a model with a'unified'architecture and only one set of pretrained weights that …
Laffnet: A lightweight adaptive feature fusion network for underwater image enhancement
Underwater image enhancement is an important low-level computer vision task for
autonomous underwater vehicles and remotely operated vehicles to explore and …
autonomous underwater vehicles and remotely operated vehicles to explore and …
Learning temporal-ordered representation for spike streams based on discrete wavelet transforms
Spike camera, a new type of neuromorphic visual sensor that imitates the sampling
mechanism of the primate fovea, can capture photons and output 40000 Hz binary spike …
mechanism of the primate fovea, can capture photons and output 40000 Hz binary spike …
Dual wavelet attention networks for image classification
Global average pooling (GAP) plays an important role in traditional channel attention.
However, there is the disadvantage of insufficient information to use the result of GAP as the …
However, there is the disadvantage of insufficient information to use the result of GAP as the …
Dawn: Direction-aware attention wavelet network for image deraining
Single image deraining aims to remove rain perturbation while restoring the clean
background scene from a rain image. However, existing methods tend to produce blurry and …
background scene from a rain image. However, existing methods tend to produce blurry and …
Deepopht: medical report generation for retinal images via deep models and visual explanation
In this work, we propose an AI-based method that intends to improve the conventional retinal
disease treatment procedure and help ophthalmologists increase diagnosis efficiency and …
disease treatment procedure and help ophthalmologists increase diagnosis efficiency and …
HIWDNet: a hybrid image-wavelet domain network for fast magnetic resonance image reconstruction
Abstract The application of Magnetic Resonance Imaging (MRI) is limited due to the long
acquisition time of k-space signals. Recently, many deep learning-based MR image …
acquisition time of k-space signals. Recently, many deep learning-based MR image …
Counting crowds in bad weather
Crowd counting has recently attracted significant attention in the field of computer vision due
to its wide applications to image understanding. Numerous methods have been proposed …
to its wide applications to image understanding. Numerous methods have been proposed …
TSRFormer: Transformer based two-stage refinement for single image shadow removal
Single-image shadow removal aims to remove undesired shadow information from captured
images. With the development of the deep convolutional neural networks, several methods …
images. With the development of the deep convolutional neural networks, several methods …
NTIRE 2023 HR nonhomogeneous dehazing challenge report
This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous
Dehazing, wherein novel techniques were proposed and evaluated on new image dataset …
Dehazing, wherein novel techniques were proposed and evaluated on new image dataset …