Deep learning for image colorization: Current and future prospects
Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …
increasing amount of researchers attention in recent years, especially deep learning-based …
SCGAN: Saliency map-guided colorization with generative adversarial network
Given a grayscale photograph, the colorization system estimates a visually plausible colorful
image. Conventional methods often use semantics to colorize grayscale images. However …
image. Conventional methods often use semantics to colorize grayscale images. However …
Thermal infrared image colorization for nighttime driving scenes with top-down guided attention
Benefitting from insensitivity to light and high penetration of foggy environments, infrared
cameras are widely used for sensing in nighttime traffic scenes. However, the low contrast …
cameras are widely used for sensing in nighttime traffic scenes. However, the low contrast …
Edge-guided multi-domain rgb-to-tir image translation for training vision tasks with challenging labels
The insufficient number of annotated thermal infrared (TIR) image datasets not only hinders
TIR image-based deep learning networks to have comparable performances to that of RGB …
TIR image-based deep learning networks to have comparable performances to that of RGB …
Tirdet: Mono-modality thermal infrared object detection based on prior thermal-to-visible translation
Cross-modality images that combine visible-infrared spectra can provide complementary
information for object detection. In particular, they are well-suited for autonomous vehicle …
information for object detection. In particular, they are well-suited for autonomous vehicle …
NIR-assisted Video Enhancement via Unpaired 24-hour Data
Low-light video enhancement in the visible (VIS) range is important yet technically
challenging, and it is likely to become more tractable by introducing near-infrared (NIR) …
challenging, and it is likely to become more tractable by introducing near-infrared (NIR) …
Nighttime Thermal Infrared Image Colorization with Feedback-based Object Appearance Learning
Stable imaging in adverse environments (eg, total darkness) makes thermal infrared (TIR)
cameras a prevalent option for night scene perception. However, the low contrast and lack of …
cameras a prevalent option for night scene perception. However, the low contrast and lack of …
Learn to recover visible color for video surveillance in a day
In silicon sensors, the interference between visible and near-infrared (NIR) signals is a
crucial problem. For all-day video surveillance, commercial camera systems usually adopt …
crucial problem. For all-day video surveillance, commercial camera systems usually adopt …
StawGAN: Structural-aware generative adversarial networks for infrared image translation
L Sigillo, E Grassucci… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper addresses the problem of translating night-time thermal infrared images, which
are the most adopted image modalities to analyze night-time scenes, to daytime color …
are the most adopted image modalities to analyze night-time scenes, to daytime color …
Memory-guided collaborative attention for nighttime thermal infrared image colorization
Nighttime thermal infrared (NTIR) image colorization, also known as translation of NTIR
images into daytime color images (NTIR2DC), is a promising research direction to facilitate …
images into daytime color images (NTIR2DC), is a promising research direction to facilitate …