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Multi-Adapter RGBT Tracking

Cheng Long Li, Andong Lu, Ai Hua Zheng, Zhengzheng Tu, Jin Tang
2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
Moreover, to reduce computational complexity for real-time demand of visual tracking, we design a parallel structure of generic adapter and modality adapter.  ...  We design three kinds of adapters within our network.  ...  In particular, we design a parallel network structure that includes a small convolution kernel (e.g., 3×3o r1 ×1) at each convolutional layer of generic adapter.  ... 
doi:10.1109/iccvw.2019.00279 dblp:conf/iccvw/LiLZTT19 fatcat:sszwbdvrhvgznhkz2rtlhpcjhq

Depth-Adaptive Computational Policies for Efficient Visual Tracking [article]

Chris Ying, Katerina Fragkiadaki
2018 arXiv   pre-print
We propose a depth-adaptive convolutional Siamese network that performs video tracking adaptively at multiple neural network depths.  ...  Current convolutional neural networks algorithms for video object tracking spend the same amount of computation for each object and video frame.  ...  Going deeper with convolutions. In CVPR, 2015. 20. L. Wang, W. Ouyang, X. Wang, and H. Lu. Visual tracking with fully convolutional networks.  ... 
arXiv:1801.00508v1 fatcat:bot2c2wthzgjfnzuz3x2n7seoi

Object-Adaptive LSTM Network for Visual Tracking

Yihan Du, Yan Yan, Si Chen, Yang Hua, Hanzi Wang
2018 2018 24th International Conference on Pattern Recognition (ICPR)  
CONCLUSION In this paper, we have proposed a novel object-adaptive LSTM network for visual object tracking.  ...  In recent years, Convolutional Neural Networks (CNNs) have been widely used in visual object tracking [1, 2, 3, 4] .  ... 
doi:10.1109/icpr.2018.8545096 dblp:conf/icpr/Du0CHW18 fatcat:mn5od3tfhrajnbvt2wiphnoijm

Deep Meta Learning for Real-Time Target-Aware Visual Tracking [article]

Janghoon Choi, Junseok Kwon, Kyoung Mu Lee
2019 arXiv   pre-print
tasks to adapt to the new appearance of a target object.  ...  In this paper, we propose a novel on-line visual tracking framework based on the Siamese matching network and meta-learner network, which run at real-time speeds.  ...  Our approach tackles the aforementioned problems by building an end-to-end visual tracking network structure incorporating Siamese matching network for target search and meta-learner network for adaptive  ... 
arXiv:1712.09153v3 fatcat:cmv2vtw5ozferhubatwvbbvprm

Graph Convolutional Tracking

Junyu Gao, Tianzhu Zhang, Changsheng Xu
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
) method for high-performance visual tracking.  ...  Tracking by siamese networks has achieved favorable performance in recent years.  ...  Target Appearance Modeling via ST-GCN Spatial-temporal structure of target object is crucial for robust visual tracking.  ... 
doi:10.1109/cvpr.2019.00478 dblp:conf/cvpr/GaoZX19 fatcat:gbvsjl2szjccnciwhajkynipwe

Learning Geometry Information of Target for Visual Object Tracking with Siamese Networks

Hang Chen, Weiguo Zhang, Danghui Yan
2021 Sensors  
In this paper, we propose a Siamese deformable cross-correlation network to model the geometric structure of target and improve the performance of visual tracking.  ...  With the guidance of the offset field, the sampling in the search image area can adapt to the deformation of the target, and realize the modeling of the geometric structure of the target.  ...  In future work, we will explore a backbone network that can model the geometric structure of the object for visual tracking. Figure 1 . 1 Figure 1.  ... 
doi:10.3390/s21237790 pmid:34883790 fatcat:z6j4herl5jfu3nydmpbzujqmsq

A Narrow Deep Learning Assisted Visual Tracking with Joint Features

Xiaoyan Qian, Daihao Zhang
2020 Mathematical Problems in Engineering  
Different from time-consuming offline training in current deep tracking, we design a simple two-layer online learning network which fuses local convolution features and global handcrafted features together  ...  to give the robust representation for visual tracking.  ...  In addition, because the CNNs are trained to recognize object classes, the deeper the network structure is, the faster the space information will lose.  ... 
doi:10.1155/2020/8659890 fatcat:6e5egqqwhjdr7ogfkrc7bdrkui

Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation [article]

Xinyu Wang, Hanxi Li, Yi Li, Fumin Shen, Fatih Porikli
2017 arXiv   pre-print
Some new deep trackers with smaller network structure achieve high efficiency while at the cost of significant decrease on precision.  ...  In this paper, we propose to transfer the feature for image classification to the visual tracking domain via convolutional channel reductions.  ...  Convolutional Neural Networks [1, 2] and Recurrent Neural Networks [3, 4] .  ... 
arXiv:1701.00561v1 fatcat:4lbjm6bimjgxbbwwfmpbzae5im

Robust Outdoor Vehicle Visual Tracking Based on k-Sparse Stacked Denoising Auto-Encoder [chapter]

Jing Xin, Xing Du, Yaqian Shi, Jian Zhang, Ding Liu
2018 Autonomous Vehicles [Working Title]  
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.  ...  neural network.  ...  All in all, the object tracking algorithm based on the convolutional neural network can effectively track object, but the network structure is relatively complex, consumes a lot of training time, and requires  ... 
doi:10.5772/intechopen.80089 fatcat:oskoxmu3qnbtldeavke2hu3joa

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
with de neural networks Xu, Jingsong Automatic Sheep Counting by Multi-object Tracking Xu, Jun Orthogonal Coded Multi-view Structured Light Inter-view Interference Elimination Xu, Linfeng  ...  Zhang, Honggang Robust Visual Tracking Via An Imbalance- Elimination Mechanism Zhang, Huiqing No-Reference Objective Quality Assessment Method of Display Products Zhang, Jian Special Cane with  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

Object tracking using a convolutional network and a structured output SVM

Junwei Li, Xiaolong Zhou, Sixian Chan, Shengyong Chen
2017 Computational Visual Media  
Object tracking has been a challenge in computer vision.  ...  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.  ...  Frame number is shown at the top left of each frame in green. 23], Li et al. used a convolutional neural network (CNN) for visual tracking with multiple image cues as inputs.  ... 
doi:10.1007/s41095-017-0087-3 fatcat:4miqlot67vhpfc2idgyag4ka5a

Classifier Adaptive Fusion: Deep Learning for Robust Outdoor Vehicle Visual Tracking

Jing Xin, Xing Du, Yaqian Shi
2019 IEEE Access  
INDEX TERMS Classifier adaptive fusion (CAF), multiple deep auto-encoder, outdoor vehicle visual tracking, particle filter.  ...  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.  ...  [26] proposed a convolution neural network model tracking framework (CNT) with two convolution layers by simplifying the structure of convolutional neural networks.  ... 
doi:10.1109/access.2019.2936433 fatcat:5iybole2brdc3dw2g7azv5ysby

Deep visual nerve tracking in ultrasound images

Mohammad Alkhatib, Adel Hafiane, Pierre Vieyres, Alain Delbos
2019 Computerized Medical Imaging and Graphics  
visualization.  ...  However, nerve tracking is a very challenging task that anesthetists can encounter due to the noise, artifacts, and nerve structure variability.  ...  Structure-aware network In general, Structure-Aware Network (SANet) [35] follows the same strategy as MDNet but with an additional recurrent neural network (RNN) based structure for improving object  ... 
doi:10.1016/j.compmedimag.2019.05.007 pmid:31349184 fatcat:ghqphllegvaw3knapi6tl4kgke

Recurrent Filter Learning for Visual Tracking [article]

Tianyu Yang, Antoni B. Chan
2017 arXiv   pre-print
Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images.  ...  The tracked object in the subsequent frames will be fed into the RNN to adapt the generated filters to appearance variations of the target.  ...  Hence, generic visual tracking should be robust enough to work with any type of object, while also being sufficiently adaptable to handle the appearance of the specific object and variations of appearance  ... 
arXiv:1708.03874v1 fatcat:i3fwad3ubzg47lkjvozh3lz5ya

A Visual Tracking Algorithm in Large-Scale Video with Convolutional Neural Networks

Ying Wang, Xiaoju Ning
2018 NeuroQuantology  
Convolutional Neural Networks (CNNs) had become a powerful model for solving many problems. In this paper, a novel visual tracking algorithm in large scale video based a trained CNN is proposed.  ...  When tracking a moving object in a new video sequence, a new network by combining the shared layers in the pre-trained CNN with a new classification layer is constructed.  ...  Conclusions In this paper, an online visual object tracking method based on improved convolution neural network is proposed.  ... 
doi:10.14704/nq.2018.16.6.1664 fatcat:krm25mwnnzffrcrnvlnfrfrbpq
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