Deep learning for visual tracking: A comprehensive survey
Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …
Deep visual tracking: Review and experimental comparison
Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …
Fast online object tracking and segmentation: A unifying approach
In this paper we illustrate how to perform both visual object tracking and semi-supervised
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …
Visual object tracking with discriminative filters and siamese networks: a survey and outlook
Accurate and robust visual object tracking is one of the most challenging and fundamental
computer vision problems. It entails estimating the trajectory of the target in an image …
computer vision problems. It entails estimating the trajectory of the target in an image …
Learning adaptive discriminative correlation filters via temporal consistency preserving spatial feature selection for robust visual object tracking
With efficient appearance learning models, discriminative correlation filter (DCF) has been
proven to be very successful in recent video object tracking benchmarks and competitions …
proven to be very successful in recent video object tracking benchmarks and competitions …
Action-decision networks for visual tracking with deep reinforcement learning
This paper proposes a novel tracker which is controlled by sequentially pursuing actions
learned by deep reinforcement learning. In contrast to the existing trackers using deep …
learned by deep reinforcement learning. In contrast to the existing trackers using deep …
High-speed tracking with kernelized correlation filters
The core component of most modern trackers is a discriminative classifier, tasked with
distinguishing between the target and the surrounding environment. To cope with natural …
distinguishing between the target and the surrounding environment. To cope with natural …
The visual object tracking vot2015 challenge results
Abstract The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-
term single-object visual trackers that do not apply pre-learned models of object …
term single-object visual trackers that do not apply pre-learned models of object …
Multi-store tracker (muster): A cognitive psychology inspired approach to object tracking
Variations in the appearance of a tracked object, such as changes in geometry/photometry,
camera viewpoint, illumination, or partial occlusion, pose a major challenge to object …
camera viewpoint, illumination, or partial occlusion, pose a major challenge to object …
Attentional correlation filter network for adaptive visual tracking
We propose a new tracking framework with an attentional mechanism that chooses a subset
of the associated correlation filters for increased robustness and computational efficiency …
of the associated correlation filters for increased robustness and computational efficiency …