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Shadow-aware image colorization
Significant advancements have been made in colorization in recent years, especially with the introduction of deep learning technology. However,...
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Temporally consistent video colorization with deep feature propagation and self-regularization learning
Video colorization is a challenging and highly ill-posed problem. Although recent years have witnessed remarkable progress in single image...
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TIC: text-guided image colorization using conditional generative model
Image colorization is a well-known problem in computer vision. However, due to the ill-posed nature of the task, image colorization is inherently...
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Automatic video colorization based on contrastive learning and optical flow
Video colorization is the process of assigning reasonable color values to gray videos. Most of the existing video colorization methods use an image...
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Colorization
There are a large number of grayscale or black-and-white images and video materials in various film, television, picture archives, medical, and other...
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Old scratched photos restoration with enhancement and colorization
Although the current deep learning-based old photos restoration work can repair scratches and structural defects, the results often have the problems...
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ParaColorizer-Realistic image colorization using parallel generative networks
Image colorization is a fascinating application of AI for information restoration. The inherently ill-posed nature of the problem increases the...
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Joint intensity–gradient guided generative modeling for colorization
This paper proposes an iterative score-based generative model for solving the automatic colorization problem. Although unsupervised learning methods...
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FAColorGAN: a dual-branch generative adversarial network for near-infrared image colorization
In addressing the issues of detail loss and poor robustness in near-infrared (NIR) image colorization tasks, this paper introduces a dual-branch...
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SPDGAN: a generative adversarial network based on SPD manifold learning for automatic image colorization
This paper addresses the automatic colorization problem, which converts a grayscale image to a colorized one. Recent deep learning approaches can...
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Image Colorization using CycleGAN with semantic and spatial rationality
The goal of image colorization is to make the generated color images closely approximate the color layout of the real color images. However, most of...
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Real-time self-supervised achromatic face colorization
Recent deep learning-based 2D face image colorization techniques demonstrate significant improvement in colorization accuracy and detail...
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Super-Attention for Exemplar-Based Image Colorization
In image colorization, exemplar-based methods use a reference color image to guide the colorization of a target grayscale image. In this article, we...
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RETRACTED ARTICLE: Memory-guided visual attention generative adversarial network for colorization of nighttime thermal infrared images
Color images offer more information and are more detail-specific compared to typical grayscale images. The frequency level of the images captured by...
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cGAN-Based Garment Line Draft Colorization Using a Garment-Line Dataset
Garment line draft is the basis of clothing design. Automatic or semi-automatic colorization of garment line draft will improve the efficiency of...
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Automatic colorization for Thangka sketch-based paintings
Thangka is a kind of ancient painting that originated from Tibetan culture. Considering its value in cultural and historical fields, digital...
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Reference-Based Line Drawing Colorization Through Diffusion Model
Line drawing colorization is an indispensable stage in the image painting process, however, traditional manual coloring requires a lot of time and...
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PCCNet: A Few-Shot Patch-Wise Contrastive Colorization Network
Few-shot colorization aims to learn a model to colorize images with little training data. Yet, existing models often fail to keep color consistency...
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ISP-GAN: inception sub-pixel deconvolution-based lightweight GANs for colorization
Though there are many encouraging reports, existing image colorization algorithms are still prone to unnatural visual distortions. We observe that...
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Semantic-Sparse Colorization Network for Deep Exemplar-Based Colorization
Exemplar-based colorization approaches rely on reference image to provide plausible colors for target gray-scale image. The key and difficulty of...