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Found 10 papers, 1 papers with code
Highlight Specular Reflection Separation based on Tensor Low-rank and Sparse Decomposition Using Polarimetric Cues
This regularization boosts the performance of the method to recover an accurate diffuse image by handling the color distortion, a common problem of chromaticity-based methods, especially in case of strong specular reflection.
Deep Polarimetric HDR Reconstruction
This paper proposes a novel learning based high-dynamic-range (HDR) reconstruction method using a polarization camera.
Online Mutual Adaptation of Deep Depth Prediction and Visual SLAM
In addition, we compare our online adaptation framework against the state-of-the-art pre-trained depth prediction CNNs to show that our online adapted depth prediction CNN outperforms the depth prediction CNNs that have been trained on a large collection of datasets.
Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior
This paper is concerned with polarimetric dense map reconstruction based on a polarization camera with the help of relative depth information as a prior.
Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition
We are interested in moving object detection in applications involving time-lapse image sequences for which current methods mistakenly group moving objects and illumination changes into foreground.
Online Illumination Invariant Moving Object Detection by Generative Neural Network
In this paper, we propose an extension of a state-of-the-art batch MOD method (ILISD) to an online/incremental MOD using unsupervised and generative neural networks, which use illumination invariant image representations.
Moving Object Detection in Time-Lapse or Motion Trigger Image Sequences Using Low-Rank and Invariant Sparse Decomposition
Next, we propose a low-rank and invariant sparse decomposition using the prior map to detect moving objects under significant illumination changes.
Fast Shadow Detection from a Single Image Using a Patched Convolutional Neural Network
In recent years, various shadow detection methods from a single image have been proposed and used in vision systems; however, most of them are not appropriate for the robotic applications due to the expensive time complexity.
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Shadow Detection
on SBU
Face Recognition using Multi-Modal Low-Rank Dictionary Learning
Face recognition has been widely studied due to its importance in different applications; however, most of the proposed methods fail when face images are occluded or captured under illumination and pose variations.
COROLA: A Sequential Solution to Moving Object Detection Using Low-rank Approximation
Extracting moving objects from a video sequence and estimating the background of each individual image are fundamental issues in many practical applications such as visual surveillance, intelligent vehicle navigation, and traffic monitoring.
