This paper presents a robust tracking algorithm using convolutional features. The proposed tracking algorithm consists of three steps: i) training ...

Abstract—This paper presents a robust tracking algorithm using convolutional features. The proposed tracking algorithm consists of three steps: i) training ...

In this paper, we present a model adaptive updating method based on a fuzzy system, which can set different updating weights on each frame to effectively deal ...

By applying the convolutional features of the pre-trained VGG-Net [12], we used an adaptive dimension reduction method to construct the feature space, then ...

Oct 22, 2024 · This paper presents an investigation of the impact of deep motion features in a tracking-by-detection framework. We further show that hand ...

Apr 22, 2020 · In this paper, we propose an adaptive structural convolutional filter model to enhance the robustness of deep regression trackers (named: ASCT).

Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of ...

This paper shows that the features extracted from a pre-trained dual stream deep convolution network can provide rich information about the target and this ...

Apr 4, 2023 · Visual object tracking using deep features has achieved great success, particularly when object appearances change in the presence of ...

In this paper, we propose to exploit the rich hierarchical features of deep convolutional neural networks to improve the accuracy and robustness of visual ...