Contrastive learning has achieved great success in skeleton-based action...
Generative models (GMs) have received increasing research interest for t...
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 ...
Recently, prompt-based learning has become a very popular solution in ma...
Existing multi-scale solutions lead to a risk of just increasing the
rec...
RGB-D object tracking has attracted considerable attention recently,
ach...
Nowadays the measure between heterogeneous data is still an open problem...
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)...
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...
In the field of action recognition, video clips are always treated as or...
The Transformer architecture has achieved rapiddevelopment in recent yea...
Sequence-to-sequence models provide a viable new approach to generative
...
Siamese approaches have achieved promising performance in visual object
...
The Discriminative Correlation Filter (CF) uses a circulant convolution
...
Recent visual object tracking methods have witnessed a continuous improv...
We propose a new Group Feature Selection method for Discriminative
Corre...
With efficient appearance learning models, Discriminative Correlation Fi...