In recent years, correlation filter-based (CF) tracking algorithms have gained momentum in
the field of visual tracking. CF tracking algorithms have achieved compelling performance by …

Existing image fusion approaches are committed to using a single deep network to solve
different image fusion problems, achieving promising performance in recent years. However …

The end-to-end image fusion framework has achieved promising performance, with
dedicated convolutional networks aggregating the multi-modal local appearance. However …

In the recent years, multicue visual tracking frameworks have been preferred over single cue
visual tracking approaches to address critical environmental challenges. In literature, it has …

We address the problem of multi-modal object tracking in video and explore various options
available for fusing the complementary information conveyed by the visible (RGB) and …

Spatial boundary effect can significantly reduce the performance of a learned discriminative
correlation filter (DCF) model. A commonly used method to relieve this effect is to extract …

Discriminative correlation filters (DCF) with powerful feature descriptors have proven to be
very effective for advanced visual object tracking approaches. However, due to the fixed …

Abstract Discriminative Correlation Filters (DCF) have been shown to achieve impressive
performance in visual object tracking. However, existing DCF-based trackers rely heavily on …

With the widespread use of deep learning in single object tracking task, mainstream tracking
algorithms treat tracking as a combined classification and regression problem. Classification …

In recent years, attention mechanisms have been widely studied in Discriminative
Correlation Filter (DCF) based visual object tracking. To realise spatial attention and …