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Deep Motion-Appearance Convolutions for Robust Visual Tracking
2019
IEEE Access
Preserved Fulltext
In this paper, we propose a deep neural network for visual tracking, namely the Motion-Appearance Dual (MADual) network, which employs a dual-branch architecture, by using deep two-dimensional (2D) and ...
INDEX TERMS Visual tracking, 3D convolutional kernels, motion-appearance. SIHANG WU received the B.S. degree from ...
To the best of our knowledge, this is the first work to introduce a deep 3D convolutional network for object tracking. 3) We propose an Inverse Temporal Training (ITT) strategy, for introducing deep motion ...
doi:10.1109/access.2019.2958405
fatcat:777v6zmdobgk5njbvsxsuv5x4i
Deep Motion Features for Visual Tracking
[article]
2016
arXiv
pre-print
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To the best of our knowledge, we are the first to propose fusing appearance information with deep motion features for visual tracking. ...
Contrary to visual tracking, deep motion features have been successfully applied for action recognition and video classification tasks. ...
In this work, we propose to combine appearance cues with deep motion information for visual tracking.
III. ...
arXiv:1612.06615v1
fatcat:jahqeo3i4rdppcfgfhdsu7hmli
A Narrow Deep Learning Assisted Visual Tracking with Joint Features
2020
Mathematical Problems in Engineering
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to give the robust representation for visual tracking. ...
A robust tracking method is proposed for complex visual sequences. ...
Many thanks are due to the original authors for providing the TB-100 dataset that is publicly available online at http://cvlab.hanyang.ac.kr/ tracker benchmark/datasets.html. ...
doi:10.1155/2020/8659890
fatcat:6e5egqqwhjdr7ogfkrc7bdrkui
STResNet_CF Tracker: The deep spatiotemporal features learning for correlation filter based robust visual object tracking
2019
IEEE Access
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Constructing a robust appearance model of the visual object is a crucial task for visual object tracking. ...
Finally, our spatiotemporal fusion feature from STResNet appearance model is incorporated into the correlation filter for robust visual object tracking. ...
This deep spatiotemporal appearance model is jointly trained offline end-to-end to achieve improved accuracy and robustness in visual object tracking. ...
doi:10.1109/access.2019.2903161
fatcat:uas76gauobcspkjwvuvy6wpevi
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks
[article]
2020
arXiv
pre-print
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tracking, which successfully exploits both appearance and motion features for model update. ...
Inspired by the human "visual tracking" capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual ...
Although motion is an important cue for video understanding, there are only a few attempts to exploit motion cues for visual object tracking in most recent deep learning based tracking approaches. ...
arXiv:2005.06536v1
fatcat:5mhnd5pb7zgupp4mzd72mjf5sm
Deep motion features for visual tracking
2016
2016 23rd International Conference on Pattern Recognition (ICPR)
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In this work, we propose to combine appearance cues with deep motion information for visual tracking. III. ...
This motivates us to investigate the fusion of standard appearance features with deep motion features for visual tracking. ...
doi:10.1109/icpr.2016.7899807
dblp:conf/icpr/GladhDKF16
fatcat:i5t6cggl3bevhlaokvwrbg2d6u
Deep Learning Trackers Review and Challenge
2019
Journal of Information Hiding and Privacy Protection
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H. (2015): Hierarchical convolutional features for visual tracking. Baek, M.; Han, B. (2016): Modeling and propagating cnns in a tree structure for visual tracking. arXiv:1608.07242. ...
.; Yang, M. (2016): Visual tracking via coarse and fine structural local sparse appearance models. ...
Network function For visual tracking, deep networks can be not only used for extracting effective features but also adopted for evaluating the candidates of the tracked object. ...
doi:10.32604/jihpp.2019.05938
fatcat:z2kq47sl25fz7fykzdhfozysge
An Analytical Review on Some Recent Advances in Deep Learning Object Tracking Approaches
2020
International Journal of Engineering Research and
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This paper presents a detailed review on some of the recent advances in Deep Learning Based Visual Object Tracking Approaches from a wide variety of algorithms often cited in research literature. ...
Visual Object tracking in real world, real time application scenarios is a complex problem, therefore, it remains a most active area of research in computer vision. ...
Described a motion net (MotionNet) to fulfill end-to-end trainable motion detection and an appearance net (AppearanceNet) for multi-scale appearance matchingto achieve object localization. [Q. ...
doi:10.17577/ijertv9is010309
fatcat:e7wny2gl35cuvfxrcfec3zxn7y
Object Tracking in Satellite Videos Based on Convolutional Regression Network with Appearance and Motion Features
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Instead of handcrafted features, both appearance features and motion features, which are extracted by pretrained deep neural networks, are used for accurate object tracking. ...
Index Terms-Convolutional neural networks (CNNs), deep learning, object tracking, satellite video. ...
By combining deep appearance and motion features, the complementary information can provide robust tracking. ...
doi:10.1109/jstars.2020.2971657
fatcat:ug4xfrsl4vfgvgsamcnjtnrzqe
A Robust Visual Tracking Algorithm Based on Spatial-Temporal Context Hierarchical Response Fusion
2018
Algorithms
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Furthermore, we proposed a re-detection activation discrimination method to improve the robustness of visual tracking in the case of tracking failure and an adaptive model update method to reduce tracking ...
Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual object tracking. ...
Hierarchical Feature of Convolution Layer The hierarchical features of deep neural networks play an important role in visual object tracking, which can enhance the robustness and accuracy of visual tracking ...
doi:10.3390/a12010008
fatcat:htv33er4hjgzlnv6n3v4m7amrm
Robust Outdoor Vehicle Visual Tracking Based on k-Sparse Stacked Denoising Auto-Encoder
[chapter]
2018
Autonomous Vehicles [Working Title]
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Robust visual tracking for outdoor vehicle is still a challenging problem due to large object appearance variations caused by illumination variation, occlusion, and fast motion. ...
vehicle tracking method under particle filter inference is further proposed to solve the problem of appearance variance during the tracking. ...
appearance in visual tracking. ...
doi:10.5772/intechopen.80089
fatcat:oskoxmu3qnbtldeavke2hu3joa
Adaptive hyper-feature fusion for visual tracking (February 2020)
2020
IEEE Access
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In this work, we propose a robust tracking algorithm based on context-aware correlation filter framework. ...
convolutional features (such as VGGNet). ...
The HCFTstar [8] effectively combines multiple layers of deep hierarchical convolutional features for visual tracking. ...
doi:10.1109/access.2020.2986157
fatcat:bvzg55ebnjekdj6y3cfbzz3hya
Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking
[article]
2021
arXiv
pre-print
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terms of precision and robustness of visual tracking. ...
This paper aims to evaluate the performance of twelve state-of-the-art ResNet-based FENs in a DCF-based framework to determine the best for visual tracking purposes. ...
[26] have investigated the fusion of handcrafted appearance features (e.g., HOG and CN) with deep RGB and motion features in the DCF-based visual tracking framework. ...
arXiv:2004.01382v2
fatcat:hsns3y46g5c7vdghlmgbzlniji
Object tracking using a convolutional network and a structured output SVM
2017
Computational Visual Media
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In this paper, we present a novel method to model target appearance and combine it with structured output learning for robust online tracking within a tracking-by-detection framework. ...
We take both convolutional features and handcrafted features into account to robustly encode the target appearance. ...
It is updated incrementally to accommodate appearance changes over time for robust visual tracking. ...
doi:10.1007/s41095-017-0087-3
fatcat:4miqlot67vhpfc2idgyag4ka5a
Classifier Adaptive Fusion: Deep Learning for Robust Outdoor Vehicle Visual Tracking
2019
IEEE Access
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However, single deep auto-encoder model would not be robust enough to represent the appearance model of outdoor vehicle for its harsh working environment, such as illumination variation, occlusion, cluttered ...
In this paper, a novel multiple-DAE-based tracking approach, that is, classifier adaptive fusion for robust outdoor vehicle visual tracking approach is proposed under particle filter framework. ...
[27] trained convolutional neural networks through online video images rather than offline images to learn complex motion features for object tracking. ...
doi:10.1109/access.2019.2936433
fatcat:5iybole2brdc3dw2g7azv5ysby
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