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Learning Low-rank and Sparse Discriminative Correlation Filters for Coarse-to-Fine Visual Object Tracking

Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jqw2pm7kwvhchpdxpcm5ryoic4" style="color: black;">IEEE transactions on circuits and systems for video technology (Print)</a> </i> &nbsp;
Discriminative correlation filter (DCF) has achieved advanced performance in visual object tracking with remarkable efficiency guaranteed by its implementation in the frequency domain.  ...  To remedy this deficiency, this paper proposes a Low-rank and Sparse DCF (LSDCF) that improves the relevance of features used by discriminative filters.  ...  Learning Low-rank and Sparse Discriminative Correlation Filters for Coarse-to-Fine Visual Object Tracking Tianyang Xu, Zhen-Hua Feng, Member, IEEE Xiao-Jun Wu, and Josef Kittler, Life Member, IEEE Abstract-Discriminative  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2019.2945068">doi:10.1109/tcsvt.2019.2945068</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rlgwtdyptfcj3g6fwhpqyqjgne">fatcat:rlgwtdyptfcj3g6fwhpqyqjgne</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200306052537/http://epubs.surrey.ac.uk/852973/1/Learning%20Low-rank%20and%20Sparse%20Discriminative%20Correlation%20Filters.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/bf/4fbfc1237ef1ed8a0d418ffbaba6dad0b583905f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2019.2945068"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Improved Hierarchical Convolutional Features for Robust Visual Object Tracking

Jinping Sun, Heng Liu
<span title="2021-01-23">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/y3fh56bfunh5fgneywwba6d4ke" style="color: black;">Complexity</a> </i> &nbsp;
First, the objective function is designed by lasso regression modeling, and a sparse, time-series low-rank filter is learned to increase the interpretability of the model.  ...  Thus, to improve the tracking performance and robustness, an improved hierarchical convolutional features model is proposed into a correlation filter framework for visual object tracking.  ...  , sparse and low-rank filter modeling, a coarse-to-fine target prediction model, and template update strategy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/6690237">doi:10.1155/2021/6690237</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h4dfgqxq6netlh2gsycpxxc3rm">fatcat:h4dfgqxq6netlh2gsycpxxc3rm</a> </span>
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Robust Visual Tracking via Hierarchical Convolutional Features [article]

Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang
<span title="2018-08-11">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To further handle the issues with scale estimation and re-detecting target objects from tracking failures caused by heavy occlusion or out-of-the-view movement, we conservatively learn another correlation  ...  Specifically, we learn adaptive correlation filters on the outputs from each convolutional layer to encode the target appearance.  ...  PROPOSED ALGORITHM We first present our approach for robust object tracking which includes extracting CNN features, learning correlation filters, and developing a coarse-to-fine search strategy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1707.03816v2">arXiv:1707.03816v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rqxytlu64na4hmwtjcahk5otou">fatcat:rqxytlu64na4hmwtjcahk5otou</a> </span>
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Low-Rank Sparse Learning for Robust Visual Tracking [chapter]

Tianzhu Zhang, Bernard Ghanem, Si Liu, Narendra Ahuja
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
As such, it casts the tracking problem as a low-rank matrix learning problem.  ...  and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which  ...  This study is supported by the research grant for the Human Sixth Sense Programme at the Advanced Digital Sciences Center from Singapores Agency for Science, Technology and Research (A STAR).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33783-3_34">doi:10.1007/978-3-642-33783-3_34</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cxvx7o5anrcsvdj2evawfeccuq">fatcat:cxvx7o5anrcsvdj2evawfeccuq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170707010523/http://vision.ai.illinois.edu/publications/zhang_eccv12.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/26/a6/26a67ecc222e39e9b10936a95d84f569607e6cef.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33783-3_34"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Robust Visual Tracking via Hierarchical Convolutional Features

Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang
<span title="">2018</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3px634ph3vhrtmtuip6xznraqi" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
To further handle the issues with scale estimation and target re-detection from tracking failures caused by heavy occlusion or moving out of the view, we conservatively learn another correlation filter  ...  Specifically, we learn adaptive correlation filters on the outputs from each convolutional layer to encode the target appearance.  ...  PROPOSED ALGORITHM We first present our approach for robust object tracking which includes extracting CNN features, learning correlation filters, and developing a coarse-to-fine search strategy.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2018.2865311">doi:10.1109/tpami.2018.2865311</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30106709">pmid:30106709</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dgpu2z5agrcc5mtxtmhvjaxtgu">fatcat:dgpu2z5agrcc5mtxtmhvjaxtgu</a> </span>
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An approach to model human appearance based on sparse representation for human tracking in surveillance

Sangeetha D
<span title="2020-04-15">2020</span> <i title="Institution of Engineering and Technology (IET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dscocsarvbb5boe7eixzypaetu" style="color: black;">IET Image Processing</a> </i> &nbsp;
Coarse and fine representation of sparse code facilitates tracking under varying scales.  ...  In this study, a robust tracking algorithm is proposed that utilises gradient orientation and fine and coarse sparse representation of the target template.  ...  Fine and coarse sparse representation, CAMShift tracking algorithm supports the tracking under various scales. Thus, it demonstrates to be a good candidate for scale variation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/iet-ipr.2018.5961">doi:10.1049/iet-ipr.2018.5961</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xvgxthgwkrd4jloup4xevtaiqe">fatcat:xvgxthgwkrd4jloup4xevtaiqe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715065427/https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2018.5961" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0f/dd/0fdd04df6486619deaa4ea325b8c463acaeb1319.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/iet-ipr.2018.5961"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

2020 Index IEEE Transactions on Image Processing Vol. 29

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
., +, TIP 2020 389-404 Fast Learning of Spatially Regularized and Content Aware Correlation Filter for Visual Tracking.  ...  ., +, TIP 2020 2820-2833 Learning Non-Local Spatial Correlations To Restore Sparse 3D Single-Photon Data. Chen, S., +, TIP 2020 3119-3131 Low-Rank Quaternion Approximation for Color Image Processing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2020.3046056">doi:10.1109/tip.2020.3046056</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/24m6k2elprf2nfmucbjzhvzk3m">fatcat:24m6k2elprf2nfmucbjzhvzk3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201224144031/https://ieeexplore.ieee.org/ielx7/83/8835130/09301460.pdf?tp=&amp;arnumber=9301460&amp;isnumber=8835130&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/56/93/5693eebc307c33915511489f6dcddcb127981534.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2020.3046056"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Learning Local Structured Correlation Filters for Visual Tracking via Spatial Joint Regularization

Chenggang Guo, Dongyi Chen, Zhiqi Huang
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
The correlation filter to be learned is divided into hierarchical local groups.  ...  Recent progress in developing robust tracking methods are mainly made upon discriminative correlation filters (DCF).  ...  [19] considered the hierarchical feature representation power of CNNs and proposed to learn adaptive correlation filters in a coarse-to-fine fashion for tracking.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2906508">doi:10.1109/access.2019.2906508</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3dqg45gfsbdjvpmgj4his3yrda">fatcat:3dqg45gfsbdjvpmgj4his3yrda</a> </span>
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Sparse Camera Network for Visual Surveillance -- A Comprehensive Survey [article]

Mingli Song, Dachent Tao, Stephen J. Maybank
<span title="2013-02-03">2013</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this review paper, we present a comprehensive survey of recent research results to address the problems of intra-camera tracking, topological structure learning, target appearance modeling, and global  ...  The analysis of visual cues in multi-camera networks enables a wide range of applications, from smart home and office automation to large area surveillance and traffic surveillance.  ...  [81] presented a February 5, 2013 DRAFT new type of correlation filter called a Minimum Output Sum of Squared Error filter to produce stable correlation filters to adapt to changes in the appearance  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1302.0446v1">arXiv:1302.0446v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j3opbzuaw5eb3c74c2ind5pmua">fatcat:j3opbzuaw5eb3c74c2ind5pmua</a> </span>
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2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jqw2pm7kwvhchpdxpcm5ryoic4" style="color: black;">IEEE transactions on circuits and systems for video technology (Print)</a> </i> &nbsp;
., TCSVT Jan. 2020 217-231 Hu, X., see Zhu, L., TCSVT Oct. 2020 3358-3371 Hu, Y., Lu, M., Xie, C., and Lu, X  ...  ., and Zeng, B., MUcast: Linear Uncoded Multiuser TCSVT Nov. 2020 4299-4308 Hu, R., see Chen, L., TCSVT Dec. 2020 4513-4525 Hu, R., see Wang, X., TCSVT Nov. 2020 4309-4320 Hu, X., see Zhang, X  ...  ., +, TCSVT Feb. 2020 376-386 Learning Low-Rank and Sparse Discriminative Correlation Filters for Coarse-to-Fine Visual Object Tracking.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tcsvt.2020.3043861">doi:10.1109/tcsvt.2020.3043861</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s6z4wzp45vfflphgfcxh6x7npu">fatcat:s6z4wzp45vfflphgfcxh6x7npu</a> </span>
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2021 Index IEEE Transactions on Multimedia Vol. 23

<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sbzicoknnzc3tjljn7ifvwpooi" style="color: black;">IEEE transactions on multimedia</a> </i> &nbsp;
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TMM 2021 4131-4142 Coarse-to-Fine CNN for Image Super-Resolution. Tian, C., +, TMM 2021 1489-1502 Collaborative Image Relevance Learning for Visual Re-Ranking.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmm.2022.3141947">doi:10.1109/tmm.2022.3141947</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lil2nf3vd5ehbfgtslulu7y3lq">fatcat:lil2nf3vd5ehbfgtslulu7y3lq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220112070754/https://ieeexplore.ieee.org/ielx7/6046/9296985/09677625.pdf?tp=&amp;arnumber=9677625&amp;isnumber=9296985&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/72/98/7298e0836b658eb4f1e43b1ba4059c50a3847dba.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmm.2022.3141947"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Deformable Parts Correlation Filters for Robust Visual Tracking [article]

Alan Lukežič, Luka Čehovin, Matej Kristan
<span title="2016-05-12">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The coarse level corresponds a root correlation filter and a novel color model for approximate object localization, while the mid-level representation is composed of the new deformable constellation of  ...  correlation filters that refine the object location.  ...  The recent revival of the matched filters [29] in the context of visual tracking has shown that efficient discriminative trackers can be designed by online learning of a correlation filter that minimizes  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1605.03720v1">arXiv:1605.03720v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/73bm2kodr5adncvwxpfnqbmxpe">fatcat:73bm2kodr5adncvwxpfnqbmxpe</a> </span>
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Tracking Noisy Targets: A Review of Recent Object Tracking Approaches [article]

Mustansar Fiaz, Arif Mahmood, Soon Ki Jung
<span title="2018-02-14">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We broadly categorize trackers into correlation filter based trackers and the others as non-correlation filter trackers.  ...  Multiple levels of additive noise are added to the Object Tracking Benchmark (OTB) 2015, and the precision and success rates of the tracking algorithms are evaluated.  ...  Taxonomy of tracking algorithms Features in Correlation Filter (CF2) for visual tracking.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.03098v2">arXiv:1802.03098v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2ygcm7gomrgffg3bo6w55kejce">fatcat:2ygcm7gomrgffg3bo6w55kejce</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200927190332/https://arxiv.org/pdf/1802.03098v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1e/6e/1e6efcbfe7a61fdb95c01ed08a1fcfa65e7cf019.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1802.03098v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Real-time and robust object tracking in video via low-rank coherency analysis in feature space

Chenglizhao Chen, Shuai Li, Hong Qin, Aimin Hao
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jm6w2xclfzguxnhmnmq5omebpi" style="color: black;">Pattern Recognition</a> </i> &nbsp;
low-rank coherency in the accompanying feature space of targeting objects, which enables real-time and robust object tracking in video while combating certain technical difficulties due to occlusion,  ...  Since the low-rank coherency implies the intrinsic co-occurring parts of different target observations, robust tracking can be achieved by employing this principle as the matching criterion even for objects  ...  IIS-0949467, IIS-1047715, and IIS-1049448).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patcog.2015.01.025">doi:10.1016/j.patcog.2015.01.025</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bdj7upc4u5hubgc6eaadl2py4e">fatcat:bdj7upc4u5hubgc6eaadl2py4e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160610100030/http://www3.cs.stonybrook.edu/~qin/research/2015-pr-robust-object-tracking.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/23/29/2329b177c71c7087013ab4bfdc3154a6ba87ff8c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patcog.2015.01.025"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Robust, Extensible, and Fast: Teamed Classifiers for Vehicle Tracking and Vehicle Re-ID in Multi-Camera Networks [article]

Abhijit Suprem, Rodrigo Alves Lima, Bruno Padilha, Joao Eduardo Ferreira, Calton Pu
<span title="2020-01-07">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We describe an implementation for vehicle tracking and vehicle re-identification (re-id), where we implement a zero-shot learning (ZSL) system that performs automated tracking of all vehicles all the time  ...  This includes performing tasks such as object detection, attribute identification, and vehicle/person tracking across different cameras without overlap.  ...  agencies and companies mentioned above.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1912.04423v2">arXiv:1912.04423v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yjpl73aqezewhmkvvut4ziet3i">fatcat:yjpl73aqezewhmkvvut4ziet3i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321085635/https://arxiv.org/pdf/1912.04423v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1912.04423v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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