Papers Image Colorization
“Image Colorization” 태그가 달린 논문 138편 · 필터 해제
Image Colorization with Generative Adversarial Networks
Over the last decade, the process of automatic image colorization has been of significant interest for several application areas including restoration of aged or degraded images. This problem is highly ill-posed due to t…
ColorizationGenerative Adversarial NetworkImage ColorizationGenerating High Quality Visible Images from SAR Images Using CNNs
We propose a novel approach for generating high quality visible-like images from Synthetic Aperture Radar (SAR) images using Deep Convolutional Generative Adversarial Network (GAN) architectures. The proposed approach is…
ColorizationGenerative Adversarial NetworkImage ColorizationVocal Bursts Intensity PredictionWeighted Nonlocal Total Variation in Image Processing
In this paper, a novel weighted nonlocal total variation (WNTV) method is proposed. Compared to the classical nonlocal total variation methods, our method modifies the energy functional to introduce a weight to balance b…
BIG-bench Machine LearningClusteringColorizationImage Colorization+1Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2
We review some of the most recent approaches to colorize gray-scale images using deep learning methods. Inspired by these, we propose a model which combines a deep Convolutional Neural Network trained from scratch with h…
ColorizationDecoderImage ColorizationMix-and-Match Tuning for Self-Supervised Semantic Segmentation
Deep convolutional networks for semantic image segmentation typically require large-scale labeled data, e.g. ImageNet and MS COCO, for network pre-training. To reduce annotation efforts, self-supervised semantic segmenta…
ColorizationImage ColorizationImage SegmentationSegmentation+2Language-Based Image Editing with Recurrent Attentive Models
We investigate the problem of Language-Based Image Editing (LBIE). Given a source image and a natural language description, we want to generate a target image by editing the source image based on the description. We prop…
ColorizationImage ColorizationImage SegmentationSegmentation+1Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning
The success of deep learning in computer vision is rooted in the ability of deep networks to scale up model complexity as demanded by challenging visual tasks. As complexity is increased, so is the need for large amounts…
ClusteringColorizationImage ColorizationRepresentation Learning+2SAR Image Colorization: Converting Single-Polarization to Fully Polarimetric Using Deep Neural Networks
A deep neural networks based method is proposed to convert single polarization grayscale SAR image to fully polarimetric. It consists of two components: a feature extractor network to extract hierarchical multi-scale spa…
ColorizationImage ColorizationProbabilistic Image Colorization
We develop a probabilistic technique for colorizing grayscale natural images. In light of the intrinsic uncertainty of this task, the proposed probabilistic framework has numerous desirable properties. In particular, our…
ColorizationImage ColorizationReal-Time User-Guided Image Colorization with Learned Deep Priors
We propose a deep learning approach for user-guided image colorization. The system directly maps a grayscale image, along with sparse, local user "hints" to an output colorization with a Convolutional Neural Network (CNN…
ColorizationImage ColorizationPoint-interactive Image ColorizationUnpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, for many tasks…
Image ColorizationImage-to-Image TranslationMultimodal Unsupervised Image-To-Image TranslationStyle Transfer+2Learning Diverse Image Colorization
Colorization is an ambiguous problem, with multiple viable colorizations for a single grey-level image. However, previous methods only produce the single most probable colorization. Our goal is to model the diversity int…
ColorizationDecoderDiversityGenerative Adversarial Network+1Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
We present a novel technique to automatically colorize grayscale images that combines both global priors and local image features. Based on Convolutional Neural Networks, our deep network features a fusion layer that all…
ColorizationImage ColorizationScene ClassificationImage Colorization Using a Deep Convolutional Neural Network
In this paper, we present a novel approach that uses deep learning techniques for colorizing grayscale images. By utilizing a pre-trained convolutional neural network, which is originally designed for image classificatio…
ColorizationGeneral Classificationimage-classificationImage Classification+3Colorful Image Colorization
Given a grayscale photograph as input, this paper attacks the problem of hallucinating a plausible color version of the photograph. This problem is clearly underconstrained, so previous approaches have either relied on s…
ColorizationDiversityImage ColorizationSelf-Supervised Image ClassificationLearning Representations for Automatic Colorization
We develop a fully automatic image colorization system. Our approach leverages recent advances in deep networks, exploiting both low-level and semantic representations. As many scene elements naturally appear according t…
ColorizationImage ColorizationRepresentation LearningLearning Large-Scale Automatic Image Colorization
We describe an automated method for image colorization that learns to colorize from examples. Our method exploits a LEARCH framework to train a quadratic objective function in the chromaticity maps, comparable to a Gaus…
ColorizationImage ColorizationEdge-aware Gradient Domain Optimization Framework for Image Filtering by Local Propagation
Gradient domain methods are popular for image processing. However, these methods even the edge-preserving ones cannot preserve edges well in some cases. In this paper, we present new constraints explicitly to better pres…
ColorizationImage Colorizationimage smoothing