Papers Colorization
“Colorization” 태그가 달린 논문 367편 · 필터 해제
Side Window Filtering
Local windows are routinely used in computer vision and almost without exception the center of the window is aligned with the pixels being processed. We show that this conventional wisdom is not universally applicable. W…
ColorizationDenoisingimage smoothingPoint-interactive Image Colorization+1Automatic Video Colorization using 3D Conditional Generative Adversarial Networks
In this work, we present a method for automatic colorization of grayscale videos. The core of the method is a Generative Adversarial Network that is trained and tested on sequences of frames in a sliding window manner. N…
ColorizationGenerative Adversarial NetworkThe Missing Data Encoder: Cross-Channel Image Completion\\with Hide-And-Seek Adversarial Network
Image completion is the problem of generating whole images from fragments only. It encompasses inpainting (generating a patch given its surrounding), reverse inpainting/extrapolation (generating the periphery given the c…
ColorizationOcclusion HandlingRepresentation LearningAutomatic Temporally Coherent Video Colorization
Greyscale image colorization for applications in image restoration has seen significant improvements in recent years. Many of these techniques that use learning-based methods struggle to effectively colorize sparse input…
ColorizationImage ColorizationImage RestorationImage-to-Image Translation+1Painting on Placement: Forecasting Routing Congestion using Conditional Generative Adversarial Nets
Physical design process commonly consumes hours to days for large designs, and routing is known as the most critical step. Demands for accurate routing quality prediction raise to a new level to accelerate hardware innov…
ColorizationTranslationUnrestricted Adversarial Examples via Semantic Manipulation
Machine learning models, especially deep neural networks (DNNs), have been shown to be vulnerable against adversarial examples which are carefully crafted samples with a small magnitude of the perturbation. Such adversar…
ColorizationImage Captioningimage-classificationImage ClassificationDeceptionNet: Network-Driven Domain Randomization
We present a novel approach to tackle domain adaptation between synthetic and real data. Instead, of employing "blind" domain randomization, i.e., augmenting synthetic renderings with random backgrounds or changing illum…
ColorizationDomain AdaptationPose EstimationSemantic SegmentationDetecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization
Image colorization achieves more and more realistic results with the increasing computation power of recent deep learning techniques. It becomes more difficult to identify the fake colorized images by human eyes. In this…
ColorizationGeneral ClassificationImage ColorizationPixelated Semantic Colorization
While many image colorization algorithms have recently shown the capability of producing plausible color versions from gray-scale photographs, they still suffer from limited semantic understanding. To address this shortc…
ColorizationImage ColorizationObjectSemantic SegmentationSurrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data
We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data. The underlying idea is to assign artificial labels …
ColorizationMedical Image AnalysisTransfer LearningSampling Using Neural Networks for colorizing the grayscale images
The main idea of this paper is to explore the possibilities of generating samples from the neural networks, mostly focusing on the colorization of the grey-scale images. I will compare the existing methods for colorizati…
ColorizationPerturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples
Despite the tremendous success of deep neural networks in various learning problems, it has been observed that adding an intentionally designed adversarial perturbation to inputs of these architectures leads to erroneous…
ClassificationColorizationGeneral ClassificationImage Colorization+1Video Colorization using CNNs and Keyframes extraction: An application in saving bandwidth
In this paper, we tackle the problem of colorization of grayscale videos to reduce bandwidth usage. For this task, we use some colored keyframes as reference images from the colored version of the grayscale video. We pro…
ColorizationSelf-Supervised Video Representation Learning with Space-Time Cubic Puzzles
Self-supervised tasks such as colorization, inpainting and zigsaw puzzle have been utilized for visual representation learning for still images, when the number of labeled images is limited or absent at all. Recently, th…
Action RecognitionColorizationRepresentation LearningSelf-Supervised Action Recognition+1Interpreting Models by Allowing to Ask
Questions convey information about the questioner, namely what one does not know. In this paper, we propose a novel approach to allow a learning agent to ask what it considers as tricky to predict, in the course of produ…
ColorizationColorUNet: A convolutional classification approach to colorization
This paper tackles the challenge of colorizing grayscale images. We take a deep convolutional neural network approach, and choose to take the angle of classification, working on a finite set of possible colors. Similarly…
ClassificationColorizationData AugmentationGeneral ClassificationThermal Infrared Colorization via Conditional Generative Adversarial Network
Transforming a thermal infrared image into a realistic RGB image is a challenging task. In this paper we propose a deep learning method to bridge this gap. We propose learning the transformation mapping using a coarse-to…
ColorizationGenerative Adversarial NetworkPoint Cloud Colorization Based on Densely Annotated 3D Shape Dataset
This paper introduces DensePoint, a densely sampled and annotated point cloud dataset containing over 10,000 single objects across 16 categories, by merging different kind of information from two existing datasets. Each …
ColorizationStructural Consistency and Controllability for Diverse Colorization
Colorizing a given gray-level image is an important task in the media and advertising industry. Due to the ambiguity inherent to colorization (many shades are often plausible), recent approaches started to explicitly mod…
ColorizationDiversityTask-Aware Image Downscaling
Image downscaling is one of the most classical problems in computer vision that aims to preserve the visual appearance of the original image when it is resized to a smaller scale. Upscaling a small image back to its orig…
ColorizationImage ColorizationSuper-Resolution