Robustness and discrimination power are two fundamental requirements in visual object
tracking. In most tracking paradigms, we find that the features extracted by the popular …

Aiming at the existing problems that object tracking algorithm fails to track under the
influence of occlusion conditions, the paper has improved the Kernel Correlation Filter …

Existing Siamese tracking methods, which are built on pair-wise matching between two
single frames, heavily rely on additional sophisticated mechanism to exploit temporal …

Variation of scales or aspect ratios has been one of the main challenges for tracking. To
overcome this challenge, most existing methods adopt either multi-scale search or anchor …

In this article, we introduce SiamMask, a framework to perform both visual object tracking
and video object segmentation, in real-time, with the same simple method. We improve the …

Current Siamese-based trackers mainly formulate the visual tracking into two indepedent
subtasks, including classification and localization. They learn the classification subnetwork …

Current oriented visual tracking depends on segmentation-driven framework brings about
expensive computation cost, which becomes the bottleneck in the practical application. This …

Image dehazing is a challenging task in computer vision. Currently, most dehazing methods
adopt the U-Net architecture that directly fuses the decoding layer with the corresponding …

Visual object tracking is an important area in computer vision, and many tracking algorithms
have been proposed with promising results. Existing object tracking approaches can be …

Reliability is an important property in the applied engineering systems, especially in visual
tracking. The supervised visual tracking method uses reliable ground truth that is manually …