Papers Colorization
“Colorization” 태그가 달린 논문 367편 · 필터 해제
LUCSS: Language-based User-customized Colourization of Scene Sketches
We introduce LUCSS, a language-based system for interactive col- orization of scene sketches, based on their semantic understanding. LUCSS is built upon deep neural networks trained via a large-scale repository of scene …
ColorizationUser-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks
Scribble colors based line art colorization is a challenging computer vision problem since neither greyscale values nor semantic information is presented in line arts, and the lack of authentic illustration-line art trai…
BenchmarkingColorizationLine Art ColorizationSketchyScene: Richly-Annotated Scene Sketches
We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dataset is created through a novel and care…
ColorizationImage RetrievalRetrievalSemantic Segmentation+1Pixel-level Semantics Guided Image Colorization
While many image colorization algorithms have recently shown the capability of producing plausible color versions from gray-scale photographs, they still suffer from the problems of context confusion and edge color bleed…
ColorizationImage ColorizationSegmentationSemantic SegmentationLearning Blind Video Temporal Consistency
Applying image processing algorithms independently to each frame of a video often leads to undesired inconsistent results over time. Developing temporally consistent video-based extensions, however, requires domain knowl…
ColorizationImage-to-Image TranslationIntrinsic Image DecompositionOptical Flow Estimation+2Deep Exemplar-based Colorization
We propose the first deep learning approach for exemplar-based local colorization. Given a reference color image, our convolutional neural network directly maps a grayscale image to an output colorized image. Rather than…
ColorizationImage RetrievalRetrievalVehicle Image Generation Going Well with The Surroundings
Since the generative neural networks have made a breakthrough in the image generation problem, lots of researches on their applications have been studied such as image restoration, style transfer and image completion. Ho…
ColorizationImage GenerationImage RestorationImage Segmentation+5The SEN1-2 Dataset for Deep Learning in SAR-Optical Data Fusion
While deep learning techniques have an increasing impact on many technical fields, gathering sufficient amounts of training data is a challenging problem in remote sensing. In particular, this holds for applications invo…
ColorizationDeep LearningImage ColorizationTracking Emerges by Colorizing Videos
We use large amounts of unlabeled video to learn models for visual tracking without manual human supervision. We leverage the natural temporal coherency of color to create a model that learns to colorize gray-scale video…
ColorizationOptical Flow EstimationSkeleton Based Action RecognitionVisual TrackingLatent Convolutional Models
We present a new latent model of natural images that can be learned on large-scale datasets. The learning process provides a latent embedding for every image in the training dataset, as well as a deep convolutional netwo…
ColorizationImage RestorationLearning on the Edge: Explicit Boundary Handling in CNNs
Convolutional neural networks (CNNs) handle the case where filters extend beyond the image boundary using several heuristics, such as zero, repeat or mean padding. These schemes are applied in an ad-hoc fashion and, bein…
ColorizationDisparity EstimationOptical Flow EstimationLearning to Color from Language
Automatic colorization is the process of adding color to greyscale images. We condition this process on language, allowing end users to manipulate a colorized image by feeding in different captions. We present two differ…
ColorizationDescriptiveColoring with Words: Guiding Image Colorization Through Text-based Palette Generation
This paper proposes a novel approach to generate multiple color palettes that reflect the semantics of input text and then colorize a given grayscale image according to the generated color palette. In contrast to existin…
ColorizationImage ColorizationSentenceMix and match networks: encoder-decoder alignment for zero-pair image translation
We address the problem of image translation between domains or modalities for which no direct paired data is available (i.e. zero-pair translation). We propose mix and match networks, based on multiple encoders and decod…
ColorizationDecoderSegmentationSemantic Segmentation+2Image 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 PredictionMultimodal Generative Models for Scalable Weakly-Supervised Learning
Multiple modalities often co-occur when describing natural phenomena. Learning a joint representation of these modalities should yield deeper and more useful representations. Previous generative approaches to multi-modal…
ColorizationEdge DetectionMachine TranslationTranslation+1Learning Image Representations by Completing Damaged Jigsaw Puzzles
In this paper, we explore methods of complicating self-supervised tasks for representation learning. That is, we do severe damage to data and encourage a network to recover them. First, we complicate each of three powerf…
ColorizationRepresentation LearningSemantic SegmentationTransfer LearningWeighted 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+1Interactive Deep Colorization With Simultaneous Global and Local Inputs
Colorization methods using deep neural networks have become a recent trend. However, most of them do not allow user inputs, or only allow limited user inputs (only global inputs or only local inputs), to control the outp…
Colorization