Contrastive learning has achieved great success in skeleton-based action...
Generative models (GMs) have received increasing research interest for t...
This paper addresses the issues of controlling and analyzing the populat...
Numerous ideas have emerged for designing fusion rules in the image fusi...
Deep learning based fusion methods have been achieving promising perform...
Symmetric Positive Definite (SPD) matrices have received wide attention ...
Deep learning-based methods have achieved significant performance for im...
Existing multi-scale solutions lead to a risk of just increasing the
rec...
RGB-D object tracking has attracted considerable attention recently,
ach...
Since MDLatLRR only considers detailed parts (salient features) of input...
Recently, Flat-LAttice Transformer (FLAT) has achieved great success in
...
Linear regression is a supervised method that has been widely used in
cl...
Nowadays the measure between heterogeneous data is still an open problem...
The traditional two-state hidden Markov model divides the high frequency...
Background: Leaning redundant and complementary relationships is a criti...
Deep learning-based image fusion approaches have obtained wide attention...
The end-to-end image fusion framework has achieved promising performance...
Visual object tracking with the visible (RGB) and thermal infrared (TIR)...
Conventional subspace learning approaches based on image gradient
orient...
The development of visual object tracking has continued for decades. Rec...
Visual object tracking with RGB and thermal infrared (TIR) spectra avail...
We address the problem of multi-modal object tracking in video and explo...
This paper presents a novel Res2Net-based fusion framework for infrared ...
This paper focuses on hyperspectral image (HSI) super-resolution that ai...
In the field of action recognition, video clips are always treated as or...
In the image fusion field, the design of deep learning-based fusion meth...
Automated neural network design has received ever-increasing attention w...
Image decomposition is a crucial subject in the field of image processin...
Deep learning is a rapidly developing approach in the field of infrared ...
Although group convolution operators are increasingly used in deep
convo...
This paper presents a Depthwise Disout Convolutional Neural Network (DD-...
During the past decade, representation-based classification methods have...
In this paper we propose a novel method for infrared and visible image f...
Siamese approaches have achieved promising performance in visual object
...
Recent years have witnessed the success of dictionary learning (DL) base...
This paper presents an improved dual channel pulse coupled neural networ...
The kernel function is introduced to solve the nonlinear pattern recogni...
Representation based classification methods have become a hot research t...
With the guaranteed discrimination and efficiency of spatial appearance
...
The Discriminative Correlation Filter (CF) uses a circulant convolution
...
In this paper, two novel methods: 2DR1-PCA and 2DL1-PCA are proposed for...
The technology of face recognition has made some progress in recent year...
Recently, sparse subspace clustering has been a valid tool to deal with
...
A novel multi-focus image fusion algorithm performed in spatial domain b...
Based on further studying the low-rank subspace clustering (LRSC) and
L2...
We consider the problem of robust face recognition in which both the tra...
Face recognition remains a hot topic in computer vision, and it is
chall...
Face recognition has been widely studied due to its importance in smart
...
Recent visual object tracking methods have witnessed a continuous improv...
Sparse-representation-based classification (SRC) has been widely studied...