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Learning Soft Mask Based Feature Fusion with Channel and Spatial Attention for Robust Visual Object Tracking

Mustansar Fiaz, Arif Mahmood, Soon Ki Jung
2020 Sensors  
The channel attention is used to identify more discriminative channels for better target representation.  ...  The proposed technique is further strengthened by integrating channel and spatial attention mechanisms.  ...  Proposed channel attention learns which deep channels should be highlighted for better target feature discrimination.  ... 
doi:10.3390/s20144021 pmid:32698339 pmcid:PMC7412361 fatcat:ve4vb6tfozb2pb5u4jl7lbdlgy

Efficient Visual Tracking with Stacked Channel-Spatial Attention Learning

Md. Maklachur Rahman, Mustansar Fiaz, Soon Ki Jung
2020 IEEE Access  
INDEX TERMS Deep learning, Siamese architecture, stacked channel-spatial attention, visual object tracking.  ...  We integrate the proposed channel and spatial attention modules to enhance tracking performance with end-to-end learning.  ...  For the spatial-first attention (SFAtt) case, we first computed spatial attention and then stacked channel attention on it.  ... 
doi:10.1109/access.2020.2997917 fatcat:hui5geq7cncizcg76hki7mbvh4

Attention-based Siamese Region Proposals Network for Visual Tracking

Fan Wang, Bo Yang, Jingting Li, Xiaopeng Hu, Zhihang Ji
2020 IEEE Access  
The attention mechanism is essentially realized by convolutional neural network. The feature optimization mainly includes spatial attention selection and channel attention selection.  ...  Specifically, the spatial attention convolutional neural network is used to learn the planar weights to enhance the foreground and suppress the interference background.  ...  It is a successful application for CNN in visual tracking.  ... 
doi:10.1109/access.2020.2991238 fatcat:qta4v5vfafdx5hmht2m25giroe

Siamese Cascaded Region Proposal Networks with Channel-Interconnection-Spatial Attention for Visual Tracking

Zhoujuan Cui, Junshe An, Qing Ye, Tianshu Cui
2020 IEEE Access  
.: Siamese Cascaded Region Proposal Networks with Channel-Interconnection-Spatial Attention for Visual Tracking 2 VOLUME XX, 2017(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k)FIGURE 7.  ...  Cui et al.: Siamese Cascaded Region Proposal Networks with Channel-Interconnection-Spatial Attention for Visual Tracking 2 VOLUME XX, 2017 (d) (e) (f) (g) (h) (i) (j) (k) (l) TABLE II  ... 
doi:10.1109/access.2020.3017179 fatcat:63t4ncbrgjczpemn6hhigipamu

HROM: Learning High-Resolution Representation and Object-Aware Masks for Visual Object Tracking

Dawei Zhang, Zhonglong Zheng, Tianxiang Wang, Yiran He
2020 Sensors  
Moreover, we exploit attention mechanisms to learn object-aware masks for adaptive feature refinement, and use deformable convolution to handle complex geometric transformations.  ...  The resulting representation is semantically richer and spatially more precise by a simple yet effective multi-scale feature fusion strategy.  ...  Channel and spatial attention mechanisms can learn 'what' and 'where' to emphasize or restrain in the channel and spatial axes, respectively.  ... 
doi:10.3390/s20174807 pmid:32858872 fatcat:m2gcbfyklzfylbpehtqnm3m5bu

Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking

Qiang Wang, Zhu Teng, Junliang Xing, Jin Gao, Weiming Hu, Stephen Maybank
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
The proposed deep architecture is trained from end to end and takes full advantage of the rich spatial temporal information to achieve robust visual tracking.  ...  However, it is still difficult to adapt an offline trained model to a target tracked online. This work presents a Residual Attentional Siamese Network (RASNet) for high performance object tracking.  ...  for visual tracking.  ... 
doi:10.1109/cvpr.2018.00510 dblp:conf/cvpr/WangTXGHM18 fatcat:5f2p5jhp55dzxigay5tqhidvza

Deformable Siamese Attention Networks for Visual Object Tracking [article]

Yuechen Yu, Yilei Xiong, Weilin Huang, Matthew R. Scott
2021 arXiv   pre-print
The self attention learns strong context information via spatial attention, and selectively emphasizes interdependent channel-wise features with channel attention.  ...  Siamese-based trackers have achieved excellent performance on visual object tracking.  ...  Conclusion We have presented new Deformable Siamese Attention Networks for visual object tracking.  ... 
arXiv:2004.06711v2 fatcat:bhvjgmnsvvdt5fobmkv7rqjgxu

Learning Reinforced Attentional Representation for End-to-End Visual Tracking [article]

Peng Gao, Qiquan Zhang, Liyi Xiao, Yan Zhang, Fei Wang
2019 arXiv   pre-print
In this paper, we propose an end-to-end network model to learn reinforced attentional representation for accurate target object discrimination and localization.  ...  Despite the fact that tremendous advances have been made by numerous recent tracking approaches in the last decade, how to achieve high-performance visual tracking is still an open problem.  ...  Some works explore attention mechanisms to highlight useful information in visual tracking. CSRDCF [34] constructs a unique spatial reliability map to constraint filters learning.  ... 
arXiv:1908.10009v2 fatcat:yr5ikhrzdjdz7bt2toxqzfrkeq

Siamese Attentional Keypoint Network for High Performance Visual Tracking [article]

Peng Gao, Yipeng Ma, Ruyue Yuan, Liyi Xiao, Fei Wang
2019 arXiv   pre-print
Firstly, a new Siamese lightweight hourglass network is specifically designed for visual tracking.  ...  Secondly, a novel cross-attentional module is utilized to leverage both channel-wise and spatial intermediate attentional information, which enhance both discriminative and localization capabilities of  ...  Maybank, Learning attentions: residual attentional siamese network for high performance online visual tracking, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp  ... 
arXiv:1904.10128v1 fatcat:ovn4s5cbdfbkllioy7fxnqxp5q

SiamCAM: A Real-Time Siamese Network for Object Tracking with Compensating Attention Mechanism

Kai Huang, Peixuan Qin, Xuji Tu, Lu Leng, Jun Chu
2022 Applied Sciences  
We propose a real-time Siamese network object tracking algorithm combined with a compensating attention mechanism to solve this problem.  ...  The Siamese-based object tracking algorithm regards tracking as a similarity matching problem.  ...  SCSAtt [39] employed channel attention and spatial attention mechanisms together to improve tracking performance with end-to-end learning.  ... 
doi:10.3390/app12083931 fatcat:6cl4lyek55gdfprygsoll7ymuy

AdaptiveWeighted Attention Network with Camera Spectral Sensitivity Prior for Spectral Reconstruction from RGB Images [article]

Jiaojiao Li, Chaoxiong Wu, Rui Song, Yunsong Li, Fei Liu
2020 arXiv   pre-print
Concretely, we investigate an adaptive weighted channel attention (AWCA) module to reallocate channel-wise feature responses via integrating correlations between channels.  ...  To conquer these issues, we propose a novel adaptive weighted attention network (AWAN) for SR, whose backbone is stacked with multiple dual residual attention blocks (DRAB) decorating with long and short  ...  Adaptive Weighted Channel Attention (AWCA) Extracting interdependencies among intermediate features is indispensable for strengthening discriminant learning power of CNNs.  ... 
arXiv:2005.09305v1 fatcat:i75u3xzivbfqdgxlaa7fics7f4

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking [article]

Xiao Wang, Xiujun Shu, Shiliang Zhang, Bo Jiang, Yaowei Wang, Yonghong Tian, Feng Wu
2022 arXiv   pre-print
The spatial and temporal recurrent neural network is used to capture the direction-aware context for accurate global attention prediction.  ...  various input images in practical tracking.  ...  It is worth mentioning that our model can also be utilized together with attention schemes, like spatial and channel attention, for robust feature learning.  ... 
arXiv:2107.10433v2 fatcat:3mxe5iidvrgbvbxdna4pwwlv74


D. Zhang, J. Lv, Z. Cheng, Y. Bai, Y. Cao
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
channel and spatial weighting on the feature maps obtained by convolution of the input image.  ...  At the same time, the backbone network model of CNN in the algorithm is adjusted, then the siamese network combined with attention mechanism for object tracking is proposed.  ...  The attention mechanism module includes channel attention module and spatial attention module.  ... 
doi:10.5194/isprs-archives-xliii-b2-2020-1315-2020 fatcat:sm2i34u5fbgqjkgn7rnwejd6w4

An Enhanced Visual Attention Siamese Network That Updates Template Features Online

Wenqiu Zhu, Guang Zou, Qiang Liu, Zhigao Zeng, Yuan Yuan
2021 Security and Communication Networks  
The method is based on a deep convolutional neural network, which integrates channel attention and spatial self-attention to improve the discriminative ability of the tracker for positive and negative  ...  In the current study, we introduce an enhanced visual attention Siamese network (ESA-Siam).  ...  tracking algorithm based on the enhanced visual attention mechanism (including channel attention, spatial self-attention, and template search collaborative attention).  ... 
doi:10.1155/2021/9719745 fatcat:5tzzjuqapbbbdd2sgpnfaanwqq

Faster MDNet for Visual Object Tracking

Qianqian Yu, Keqi Fan, Yiyang Wang, Yuhui Zheng
2022 Applied Sciences  
Simultaneously, we implement an adaptive, spatial pyramid pooling layer for reducing model complexity and accelerating the tracking speed.  ...  To improve the tracking accuracy, a channel attention module is introduced to our method. We also design domain adaptation components to obtain more generic features.  ...  CBAM [33] combined channel attention and spatial attention, which improved computational efficiency by decoupling attention maps between channel dimensions and spatial dimensions.  ... 
doi:10.3390/app12052336 fatcat:vj767tq2hzeydbbxvkzzknbowq
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