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Found 33 papers, 23 papers with code
CCMNet: Leveraging Calibrated Color Correction Matrices for Cross-Camera Color Constancy
Our method leverages pre-calibrated color correction matrices (CCMs) available on ISPs that map the camera's raw color space to a standard space (e. g., CIE XYZ).
Multispectral Demosaicing via Dual Cameras
Multispectral (MS) images capture detailed scene information across a wide range of spectral bands, making them invaluable for applications requiring rich spectral data.
Small Contributions, Small Networks: Efficient Neural Network Pruning Based on Relative Importance
Recent advancements have scaled neural networks to unprecedented sizes, achieving remarkable performance across a wide range of tasks.
What Do You See? Enhancing Zero-Shot Image Classification with Multimodal Large Language Models
Using multimodal LLMs, we generate comprehensive textual representations from input images.
Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs
Neural-based end-to-end learnable ISPs offer promising advancements, potentially replacing traditional ISPs with their ability to adapt without requiring extensive tuning for each new camera model, as is often the case for nearly every module in traditional ISPs.
Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging
Within camera ISP pipeline, illuminant estimation is a crucial step aiming to estimate the color of the global illuminant in the scene.
Multi-View Motion Synthesis via Applying Rotated Dual-Pixel Blur Kernels
In this work, we follow the trend of rendering the NIMAT effect by introducing a modification on the blur synthesis procedure in portrait mode.
Auto White-Balance Correction for Mixed-Illuminant Scenes
Auto white balance (AWB) is applied by camera hardware at capture time to remove the color cast caused by the scene illumination.
Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning
Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network's ability to learn to deblur the image.
Image color correction, enhancement, and editing
This thesis presents methods and approaches to image color correction, color enhancement, and color editing.
CAMS: Color-Aware Multi-Style Transfer
A nice feature of our method is that it enables the users to manually select the color associations between the target style and content image for more transfer flexibility.
Semi-Supervised Raw-to-Raw Mapping
This paper focuses on the task of mapping between different sensor raw-RGB color spaces.
Cross-Camera Convolutional Color Constancy
We present "Cross-Camera Convolutional Color Constancy" (C5), a learning-based method, trained on images from multiple cameras, that accurately estimates a scene's illuminant color from raw images captured by a new camera previously unseen during training.
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms
This goal has led to significant interest in methods that can intuitively control the appearance of images generated by GANs.
AIM 2020: Scene Relighting and Illumination Estimation Challenge
The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i. e., light source position).
Interactive White Balancing for Camera-Rendered Images
This is because RAW images have no photo-rendering operations applied and photo-editing software is able to apply WB and other photo-finishing procedures to render the final image.
CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks
Because of this, a number of methods have been proposed to "unprocess" nonlinear images back to a raw-RGB state.
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
This challenge is based on a newly collected validation and testing image datasets, and hence, named SIDD+.
Deep White-Balance Editing
The ISP rendering begins with a white-balance procedure that is used to remove the color cast of the scene's illumination.
Learning Multi-Scale Photo Exposure Correction
In contrast, our proposed method targets both over- and underexposure errors in photographs.
Ranked #4 on
Image Enhancement
on Exposure-Errors
What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performance
There is active research targeting local image manipulations that can fool deep neural networks (DNNs) into producing incorrect results.
Sensor-Independent Illumination Estimation for DNN Models
Our learned space retains the linear property of the original sensor raw-RGB space and allows unseen camera sensors to be used on a single DNN model trained on this working space.
When Color Constancy Goes Wrong: Correcting Improperly White-Balanced Images
The challenge lies not in identifying what the correct white balance should have been, but in the fact that the in-camera white-balance procedure is followed by several camera-specific nonlinear color manipulations that make it challenging to correct the image's colors in post-processing.
Image Recoloring Based on Object Color Distributions
We present a method to perform automatic image recoloring based on the distribution of colors associated with objects present in an image.
As-projective-as-possible bias correction for illumination estimation algorithms
Recent work by Finlayson, Interface Focus, 2018 showed that a bias correction function can be formulated as a projective transform because the magnitude of the R, G, B illumination vector does not matter to the AWB procedure.
Image Posterization Using Fuzzy Logic and Bilateral Filter
Image posterization is converting images with a large number of tones into synthetic images with distinct flat areas and a fewer number of tones.
Semantic White Balance: Semantic Color Constancy Using Convolutional Neural Network
The goal of computational color constancy is to preserve the perceptive colors of objects under different lighting conditions by removing the effect of color casts caused by the scene's illumination.
11K Hands: Gender recognition and biometric identification using a large dataset of hand images
In this work, we propose a large dataset of human hand images (dorsal and palmar sides) with detailed ground-truth information for gender recognition and biometric identification.
The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques
Compared with existing OMR systems, the proposed system has the least constraints and achieves a high accuracy.
Can We Boost the Power of the Viola-Jones Face Detector Using Pre-processing? An Empirical Study
In this paper, we study the influence of a set of blind pre-processing methods on the face detection rate using the Viola-Jones algorithm.
AFIF4: Deep Gender Classification based on AdaBoost-based Fusion of Isolated Facial Features and Foggy Faces
Gender classification aims at recognizing a person's gender.
Can We See Photosynthesis? Magnifying the Tiny Color Changes of Plant Green Leaves Using Eulerian Video Magnification
In this paper, we aim to detect the degree of animation of plants based on the magnification of the small color changes in the plant's green leaves using the Eulerian video magnification.
MPB: A modified Poisson blending technique
Image cloning has many useful applications, such as removing unwanted objects, fixing damaged parts of images, and panorama stitching.
