Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset
Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …
moving objects. Recent research on problem formulations based on decomposition into low …
[HTML][HTML] Spatial imputation for air pollutants data sets via low rank matrix completion algorithm
Incomplete observation of hourly air-pollutants concentration data is a common issue
existing in urban air quality monitoring networks. This research proposes a spatial …
existing in urban air quality monitoring networks. This research proposes a spatial …
3d face morphable models" in-the-wild"
Abstract 3D Morphable Models (3DMMs) are powerful statistical models of 3D facial shape
and texture, and among the state-of-the-art methods for reconstructing facial shape from …
and texture, and among the state-of-the-art methods for reconstructing facial shape from …
Bilinear factor matrix norm minimization for robust PCA: Algorithms and applications
The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-
level vision have proven effective priors for many applications such as background …
level vision have proven effective priors for many applications such as background …
Deep neural network augmentation: Generating faces for affect analysis
This paper presents a novel approach for synthesizing facial affect; either in terms of the six
basic expressions (ie, anger, disgust, fear, joy, sadness and surprise), or in terms of valence …
basic expressions (ie, anger, disgust, fear, joy, sadness and surprise), or in terms of valence …
Robust quaternion matrix completion with applications to image inpainting
In this paper, we study robust quaternion matrix completion and provide a rigorous analysis
for provable estimation of quaternion matrix from a random subset of their corrupted entries …
for provable estimation of quaternion matrix from a random subset of their corrupted entries …
Exact decomposition of joint low rankness and local smoothness plus sparse matrices
It is known that the decomposition in low-rank and sparse matrices (L+ S for short) can be
achieved by several Robust PCA techniques. Besides the low rankness, the local …
achieved by several Robust PCA techniques. Besides the low rankness, the local …
[图书][B] Handbook of robust low-rank and sparse matrix decomposition: Applications in image and video processing
Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image
and Video Processing shows you how robust subspace learning and tracking by …
and Video Processing shows you how robust subspace learning and tracking by …
Trace norm regularized CANDECOMP/PARAFAC decomposition with missing data
In recent years, low-rank tensor completion (LRTC) problems have received a significant
amount of attention in computer vision, data mining, and signal processing. The existing …
amount of attention in computer vision, data mining, and signal processing. The existing …
[PDF][PDF] Robust Low-Tubal-Rank Tensor Completion via Convex Optimization.
Q Jiang, M Ng - IJCAI, 2019 - ijcai.org
This paper considers the problem of recovering multidimensional array, in particular third-
order tensor, from a random subset of its arbitrarily corrupted entries. Our study is based on …
order tensor, from a random subset of its arbitrarily corrupted entries. Our study is based on …