Papers Color Constancy
“Color Constancy” 태그가 달린 논문 114편 · 필터 해제
ADCC: An Effective and Intelligent Attention Dense Color Constancy System for Studying Images in Smart Cities
As a novel method eliminating chromatic aberration on objects, computational color constancy has becoming a fundamental prerequisite for many computer vision applications. Among algorithms performing this task, the learn…
Color ConstancyINTEL-TAU: A Color Constancy Dataset
In this paper, we describe a new large dataset for illumination estimation. This dataset, called INTEL-TAU, contains 7022 images in total, which makes it the largest available high-resolution dataset for illumination est…
Color ConstancyFew-Shot Camera-Adaptive Color ConstancyImage DeclippingMulti-target regressionFast Fourier Color Constancy and Grayness Index for ISPA Illumination Estimation Challenge
We briefly introduce two submissions to the Illumination Estimation Challenge, in the Int'l Workshop on Color Vision, affiliated to the 11th Int'l Symposium on Image and Signal Processing and Analysis. The Fourier-transf…
Color ConstancyColor Cerberus
Simple convolutional neural network was able to win ISISPA color constancy competition. Partial reimplementation of (Bianco, 2017) neural architecture would have shown even better results in this setup.
Color ConstancyIlluminant Chromaticity Estimation from Interreflections
Reliable estimation of illuminant chromaticity is crucial for simulating color constancy and for white balancing digital images. However, estimating illuminant chromaticity from a single image is an ill-posed task, in ge…
Color ConstancyBag of Color Features For Color Constancy
In this paper, we propose a novel color constancy approach, called Bag of Color Features (BoCF), building upon Bag-of-Features pooling. The proposed method substantially reduces the number of parameters needed for illumi…
Color ConstancyColor Constancy Convolutional Autoencoder
In this paper, we study the importance of pre-training for the generalization capability in the color constancy problem. We propose two novel approaches based on convolutional autoencoders: an unsupervised pre-training a…
Color ConstancyUnsupervised Pre-trainingWhen Color Constancy Goes Wrong: Correcting Improperly White-Balanced Images
This paper focuses on correcting a camera image that has been improperly white-balanced. This situation occurs when a camera's auto white balance fails or when the wrong manual white-balance setting is used. Even after d…
Color ConstancyQuasi-Unsupervised Color Constancy
We present here a method for computational color constancy in which a deep convolutional neural network is trained to detect achromatic pixels in color images after they have been converted to grayscale. The method does …
Color ConstancyConvolutional Neural Networks Can Be Deceived by Visual Illusions
Visual illusions teach us that what we see is not always what is represented in the physical world. Their special nature make them a fascinating tool to test and validate any new vision model proposed. In general, curren…
Color ConstancyDeblurringDenoisingImage Deblurring+1Dichromatic Model Based Temporal Color Constancy for AC Light Sources
Existing dichromatic color constancy approach commonly requires a number of spatial pixels which have high specularity. In this paper, we propose a novel approach to estimate the illuminant chromaticity of AC light sourc…
Color ConstancyDeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks
Computational color constancy refers to the estimation of the scene illumination and makes the perceived color relatively stable under varying illumination. In the past few years, deep Convolutional Neural Networks (CNNs…
Color ConstancyLearning Matchable Image Transformations for Long-term Metric Visual Localization
Long-term metric self-localization is an essential capability of autonomous mobile robots, but remains challenging for vision-based systems due to appearance changes caused by lighting, weather, or seasonal variations. W…
Color ConstancyVisual LocalizationCroP: Color Constancy Benchmark Dataset Generator
Implementing color constancy as a pre-processing step in contemporary digital cameras is of significant importance as it removes the influence of scene illumination on object colors. Several benchmark color constancy dat…
Color ConstancyThe Past and the Present of the Color Checker Dataset Misuse
The pipelines of digital cameras contain a part for computational color constancy, which aims to remove the influence of the illumination on the scene colors. One of the best known and most widely used benchmark datasets…
Color ConstancyColor Constancy by GANs: An Experimental Survey
In this paper, we formulate the color constancy task as an image-to-image translation problem using GANs. By conducting a large set of experiments on different datasets, an experimental survey is provided on the use of d…
Color ConstancyImage-to-Image TranslationSurveyTranslationSpectral Illumination Correction: Achieving Relative Color Constancy Under the Spectral Domain
Achieving color constancy between and within images, i.e., minimizing the color difference between the same object imaged under nonuniform and varied illuminations is crucial for computer vision tasks such as colorimetri…
Camera CalibrationColor ConstancyObject RecognitionThe Visual Centrifuge: Model-Free Layered Video Representations
True video understanding requires making sense of non-lambertian scenes where the color of light arriving at the camera sensor encodes information about not just the last object it collided with, but about multiple mediu…
Color ConstancymodelVideo UnderstandingFormulating Camera-Adaptive Color Constancy as a Few-shot Meta-Learning Problem
Digital camera pipelines employ color constancy methods to estimate an unknown scene illuminant, in order to re-illuminate images as if they were acquired under an achromatic light source. Fully-supervised learning appro…
Color ConstancyFew-Shot Camera-Adaptive Color ConstancyMeta-LearningConvolutional Neural Networks Deceived by Visual Illusions
Visual illusions teach us that what we see is not always what it is represented in the physical world. Its special nature make them a fascinating tool to test and validate any new vision model proposed. In general, curre…
Color ConstancyDeblurringDenoisingImage Deblurring+1