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Target-Aware Tracking with Long-term Context Attention
[article]
2023
arXiv
pre-print
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To alleviate the above problem, we propose a long-term context attention (LCA) module that can perform extensive information fusion on the target and its context from long-term frames, and calculate the ...
By embedding the LCA module in Transformer, we build a powerful online tracker with a target-aware backbone, termed as TATrack. ...
Method Long-term Contextual Attention (LCA) In this section, we first introduce the proposed Long-term Contextual Attention (LCA) module, which is designed for integrating the information of target and ...
arXiv:2302.13840v1
fatcat:ye4rojm4lvbp3apvemtzl3kqhu
Object Tracking Based on Global Context Attention
2021
International Journal of Cognitive Informatics and Natural Intelligence
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To remedy this, this article proposes an object-tracking method by introducing the Global Context attention module into the Multi-Domain Network (MDNet) tracker. ...
Previous research has shown that tracking algorithms cannot capture long-distance information and lead to the loss of the object when the object was deformed, the illumination changed, and the background ...
In terms of multi-attention in visual tracking, Chen et al. (2019) use an attention mechanism with long short-term memory units to capture multilevel visual attention in a historical context. ...
doi:10.4018/ijcini.287595
fatcat:kznox2z4jvdbvmtw4rv2xomejm
Visual Tracking by TridentAlign and Context Embedding
[article]
2020
arXiv
pre-print
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However, extensive scale variations of the target object and distractor objects with similar categories have consistently posed challenges in visual tracking. ...
Meanwhile, context embedding module aims to discriminate the target from distractor objects by accounting for the global context information among objects. ...
Long-term trackers : With growing interest on long-term visual tracking tasks and more benchmarks becoming available to the public [10, 45, 12] , tracking algorithms focused on solving long-term tracking ...
arXiv:2007.06887v1
fatcat:laskvl6xl5egliwmy53w22b544
SiamMan: Siamese Motion-aware Network for Visual Tracking
[article]
2020
arXiv
pre-print
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Meanwhile, we introduce the global context module into the localization branch to capture long-range dependency for more robustness in large displacement of target. ...
In this paper, we present a novel siamese motion-aware network (SiamMan) for visual tracking, which consists of the siamese feature extraction subnetwork, followed by the classification, regression, and ...
It includes 35 sequences with 14, 687 frames. Each sequence contains 12 long-term target disappearing cases in average. ...
arXiv:1912.05515v2
fatcat:sc3y2eo37bdpdaw5uvq3f353ki
Learning Cascaded Context-Aware Framework for Robust Visual Tracking
2019
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
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Depending on the output of these two networks-the final context-aware map, we can generate the bounding box of the target flexibly. ...
The first network pays attention to the most discriminative information within the whole context and coarser structure of the target, the second network focuses on the self-structure information of the ...
To this end, LSTM is selected to handle this long-term dependency. ...
doi:10.1109/iccvw.2019.00010
dblp:conf/iccvw/Ma019
fatcat:ogpqub5ptjbzpkjjdxpbtgjuoe
Leveraging Negative Signals with Self-Attention for Sequential Music Recommendation
[article]
2023
arXiv
pre-print
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2024 accepted arXiv:2309.11623v2 fatcat:uz4ysz5bnngo7ixig45654723e
long and short-term user history and item features; however, most of these studies focus on long-form content domains (retail, movie, etc.) rather than short-form, such as music. ...
We additionally propose a contrastive learning task to incorporate negative feedback (e.g skipped tracks) to promote positive hits and penalize negative hits. ...
Multiple avenues for future work arise, namely the inclusion of long-term user profiles for better modelling of long term and changing user-taste. ...
arXiv:2309.11623v1
fatcat:jw7yb723qfhatjdyctcdm6nefi
Beyond Visual Cues: Synchronously Exploring Target-Centric Semantics for Vision-Language Tracking
[article]
2024
arXiv
pre-print
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2023 pre-print arXiv:2311.17085v1 fatcat:io6rb2b57zdnxgmrbl3nqvkvmy
Specifically, we propose the first Synchronous Learning Backbone (SLB) for VL tracking, which consists of two novel modules: the Target Enhance Module (TEM) and the Semantic Aware Module (SAM). ...
Single object tracking aims to locate one specific target in video sequences, given its initial state. ...
LaSOT, a comprehensive benchmark consists of long sequences for visual tracking, whose primary challenge lies in the robustness of long-term tracking. ...
arXiv:2311.17085v2
fatcat:zmrocanalvb4tc6wirueb24hwa
Distractor-Aware Siamese Networks for Visual Object Tracking
[chapter]
2018
Lecture Notes in Computer Science
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In this paper, we focus on learning distractor-aware Siamese networks for accurate and long-term tracking. To this end, features used in traditional Siamese trackers are analyzed at first. ...
In addition, we extend the proposed approach for long-term tracking by introducing a simple yet effective local-to-global search region strategy. ...
✦ ✦ ✦ distractor-aware updating? ✦ ✦ long-term tracking module? ✦ ...
doi:10.1007/978-3-030-01240-3_7
fatcat:g2fjqyj7uzg5li2afim5kegy64
MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking
[article]
2022
arXiv
pre-print
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The spatial and temporal recurrent neural network is used to capture the direction-aware context for accurate global attention prediction. ...
To address issues caused by heavy occlusion, fast motion and out-of-view, we propose to conduct a joint local and global search by exploiting a new direction-aware target driven attention mechanism. ...
An overview of our direction-aware target driven attention network (termed daTANet) can be found in Fig. 4 . ...
arXiv:2107.10433v2
fatcat:3mxe5iidvrgbvbxdna4pwwlv74
Online Visual Tracking with One-Shot Context-Aware Domain Adaptation
[article]
2021
arXiv
pre-print
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The domain adaptation approach is backboned with only an off-the-shelf deep model. ...
However, the trackers adopting this policy fail to fully leverage the discriminative context of the background areas. ...
DaSiamRPN [9] attempts to deal with the data imbalance issue in the SiamRPN and boosts its adaptability and also extends SiamRPN to the long-term tracking with local-to-global search region strategy. ...
arXiv:2008.09891v2
fatcat:2o57dm6rozggrin6pun6fwwtpq
Pay Attention to How You Drive: Safe and Adaptive Model-Based Reinforcement Learning for Off-Road Driving
[article]
2023
arXiv
pre-print
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The SIT uses attention mechanisms to distill state-transition observations from the target system into a context vector, which provides an abstraction for its target dynamics. ...
system dynamics improves with more observations. ...
The SIT uses attention mechanisms to distill state-transition observations from the target system into a context vector, which provides an abstraction for its target dynamics. ...
arXiv:2310.08674v1
fatcat:5s43mj4p4zgsndjvblrdshiwbe
COMET: Context-Aware IoU-Guided Network for Small Object Tracking
[article]
2020
arXiv
pre-print
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The proposed network fully exploits target-related information by multi-scale feature learning and attention modules. ...
To address this problem, we introduce a context-aware IoU-guided tracker (COMET) that exploits a multitask two-stream network and an offline reference proposal generation strategy. ...
Motivated by the issues and also recent advances in small object detection, this paper proposes a Context-aware iOu-guided network for sMall objEct Tracking (COMET). ...
arXiv:2006.02597v3
fatcat:m2jmlmdryvbplfv6xkhgm6jxzi
Beyond Background-Aware Correlation Filters: Adaptive Context Modeling by Hand-Crafted and Deep RGB Features for Visual Tracking
[article]
2021
arXiv
pre-print
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In recent years, the background-aware correlation filters have achie-ved a lot of research interest in the visual target tracking. ...
When the HOG-based response map is not reliable, or the context region has a low semantic similarity with prior regions, the proposed method constructs the CNN context model to improve the target region ...
Compliance with Ethical Standards: All authors declare that they have no conflict of interest. ...
arXiv:2004.02932v2
fatcat:dbjgzsequvcpxgq2qlilv6rmbi
ProContEXT: Exploring Progressive Context Transformer for Tracking
[article]
2023
arXiv
pre-print
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2023 pre-print arXiv:2210.15511v3 fatcat:zfcupind7jgbnizpl3mhxsq4kyOther Versions
Specifically, ProContEXT leverages a context-aware self-attention module to encode the spatial and temporal context, refining and updating the multi-scale static and dynamic templates to progressively ...
Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template. ...
Despite expanding long-term temporal and multiscale spatial information, ProContEXT can perform context encoding and tracking in real-time at 54.3 FPS. ...
arXiv:2210.15511v4
fatcat:nswy6ygmsrdztihwb3epwtb5ze
TMDiMP: Temporal Memory Guided Discriminative Tracker for UAV Object Tracking
2022
Remote Sensing
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Inspired by the self-attention mechanism in Transformer, a novel memory-aware attention mechanism is embedded into TMDiMP, which can generate discriminative features of small objects and overcome the object-forgetting ...
Moreover, to capture objects continuously, a UAV camera must constantly move with the object. The above two reasons are usual causes of object-tracking failures. ...
In the future, we will pay more attention to data with multiple challenging attributes, such as long-term object blur and occlusion. ...
doi:10.3390/rs14246351
fatcat:ix32rffkxnbjxmfxcmeklhdeqq
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