Fully-Convolutional Siamese Networks for Object Tracking

ImageNet classification with deep convolutional neural networks

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ImageNet Large Scale Visual Recognition Challenge

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818 · see citing works

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

He, K., Zhang, X., Ren, S., & Sun, J. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.123 · Cited by 19,741 · see citing works

FaceNet: A unified embedding for face recognition and clustering

Schroff, F., Kalenichenko, D., & Philbin, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298682 · Cited by 15,267 · see citing works

DeepFace: Closing the Gap to Human-Level Performance in Face Verification

Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.220 · Cited by 6,542 · see citing works

High-Speed Tracking with Kernelized Correlation Filters

Henriques, J. F., Caseiro, R., Martins, P., & Batista, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2345390 · Cited by 5,753 · see citing works

Deep Face Recognition

Parkhi, O. M., Vedaldi, A., & Zisserman, A. (2015) · Procedings of the British Machine Vision Conference 2015 · doi:10.5244/c.29.41 · Cited by 5,479 · see citing works

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2014.131 · Cited by 4,451 · see citing works

Flownet: Learning optical flow with convolutional networks

Dosovitskiy, A., Fischer, P., Ilg, E., Hausser, P., Hazirbas, C., Golkov, V., Smagt, P. V. D., Cremers, D., & Brox, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.316 · Cited by 4,313 · see citing works

Online Object Tracking: A Benchmark

Wu, Y., Lim, J., & Yang, M.-H. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.312 · Cited by 4,138 · see citing works

Siamese Neural Networks for One-shot Image Recognition

Koch, G. E., Zemel, R. S., & Salakhutdinov, R. (2015) · Cited by 3,712 · see citing works

Tracking-Learning-Detection

Kalal, Z., Mikolajczyk, K., & Matas, J. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.239 · Cited by 3,357 · see citing works

Learning Multi-domain Convolutional Neural Networks for Visual Tracking

Nam, H., & Han, B. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.465 · Cited by 2,806 · see citing works

MatConvNet: Convolutional Neural Networks for MATLAB

Vedaldi, A., & Lenc, K. (2015) · Proceedings of the 23rd ACM international conference on Multimedia · doi:10.1145/2733373.2807412 · Cited by 2,444 · see citing works

SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK

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Learning Spatially Regularized Correlation Filters for Visual Tracking

Danelljan, M., Hager, G., Khan, F. S., & Felsberg, M. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.490 · Cited by 2,171 · see citing works

Accurate Scale Estimation for Robust Visual Tracking

Danelljan, M., Hager, G., Khan, F. S., & Felsberg, M. (2014) · British Machine Vision Conference (BMVC) · doi:10.5244/c.28.65 · Cited by 2,145 · see citing works

Signature Verification Using A "Siamese" Time Delay Neural Network

BROMLEY, J., BENTZ, J. W., BOTTOU, L., GUYON, I., LECUN, Y., MOORE, C., SÄCKINGER, E., & SHAH, R. (1993) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001493000339 · Cited by 2,077 · see citing works

Struck: Structured output tracking with kernels

Hare, S., Saffari, A., & Torr, P. H. S. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126251 · Cited by 1,831 · see citing works

Staple: Complementary Learners for Real-Time Tracking

Bertinetto, L., Valmadre, J., Golodetz, S., Mikšík, O., & Torr, P. H. S. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.156 · Cited by 1,825 · see citing works

Hierarchical Convolutional Features for Visual Tracking

Ma, C., Huang, J., Yang, X., & Yang, M. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.352 · Cited by 1,811 · see citing works

Learning to compare image patches via convolutional neural networks

Zagoruyko, S., & Nikos Komodakis, A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299064 · Cited by 1,540 · see citing works

Visual Tracking: An Experimental Survey

Smeulders, A. W. M., Chu, D. M., Cucchiara, R., Calderara, S., Dehghan, A., & Shah, M. A. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.230 · Cited by 1,527 · see citing works

A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration

Li, Y., & Zhu, J. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16181-5_18 · Cited by 1,461 · see citing works

Siamese Instance Search for Tracking

Tao, R., Gavves, E., & Smeulders, A. W. M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.158 · Cited by 1,208 · see citing works

Learning to Track at 100 FPS with Deep Regression Networks

Held, D., Thrun, S., & Savarese, S. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_45 · Cited by 1,199 · see citing works

Convolutional Features for Correlation Filter Based Visual Tracking

Danelljan, M., Hager, G., Khan, F. S., & Felsberg, M. (2015) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2015.84 · Cited by 1,002 · see citing works

Visual Tracking with Fully Convolutional Networks

Wang, L., Ouyang, W., Wang, X., & Lu, H. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.357 · Cited by 1,001 · see citing works

Long-term correlation tracking

Ma, C., Yang, X., Zhang, C., & Yang, M. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299177 · Cited by 980 · see citing works

The Visual Object Tracking VOT2015 Challenge Results

Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Zajc, L. Č., Vojír, T., Häger, G., Lukežič, A., Eldesokey, A., et al. (2015) · 2015 IEEE International Conference on Computer Vision Workshop (ICCVW) · doi:10.1109/iccvw.2015.79 · Cited by 895 · see citing works

FlowNet: Learning Optical Flow with Convolutional NetworksPreprint

Fischer, P., Dosovitskiy, A., Ilg, E., Haeusser, P., Hazırbaş, C., Golkov, V., van der Smagt, P., Cremers, D., & Brox, T. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1504.06852 · Cited by 814 · see citing works

Discriminative Learning of Deep Convolutional Feature Point Descriptors

Simo‐Serra, E., Trulls, E., Ferraz, L., Kokkinos, I., Fua, P., & Moreno-Noguer, F. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.22 · Cited by 804 · see citing works

Efficient Deep Learning for Stereo Matching

Luo, W., Schwing, A. G., & Urtasun, R. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.614 · Cited by 764 · see citing works

The Visual Object Tracking VOT2014 Challenge Results

Kristan, M., Pflugfelder, R. P., Leonardis, A., Matas, J., Zajc, L. Č., Nebehay, G., Vojíř, T., Fernández, G., Lukežič, A., Dimitriev, A., et al. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16181-5_14 · Cited by 606 · see citing works

In defense of color-based model-free tracking

Possegger, H., Mauthner, T., & Bischof, H. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298823 · Cited by 370 · see citing works

Transferring Rich Feature Hierarchies for Robust Visual TrackingPreprint

Wang, N., Li, S., Gupta, A. K., & Yeung, D. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1501.04587 · Cited by 293 · see citing works

Object Tracking via Dual Linear Structured SVM and Explicit Feature Map

Ning, J., Yang, J., Jiang, S., Lei Zhang, A., & Yang, M. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.462 · Cited by 250 · see citing works

Visual Tracking Using Attention-Modulated Disintegration and Integration

Choi, J., Chang, H. J., Jeong, J., Demiris, Y., & Choi, J. Y. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.468 · Cited by 191 · see citing works

Learning Where to Attend with Deep Architectures for Image Tracking

Denil, M., Bazzani, L., Larochelle, H., & de Freitas, N. (2012) · Neural Computation · doi:10.1162/neco_a_00312 · Cited by 180 · see citing works

NUS-PRO: A New Visual Tracking Challenge

Li, A., Lin, M., Wu, Y., Yang, M., & Yan, S. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2417577 · Cited by 174 · see citing works

Online Object Tracking with Proposal Selection

Yang, H., Alahari, K., & Schmid, C. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.354 · Cited by 106 · see citing works

Once for All: A Two-Flow Convolutional Neural Network for Visual Tracking

Chen, K., & Tao, W. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2757061 · Cited by 94 · see citing works

Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data

Wang, N., & Yeung, D. (2014) · Rare & Special e-Zone (The Hong Kong University of Science and Technology) · Cited by 91 · see citing works

RATM: Recurrent Attentive Tracking Model

Kahou, S. E., Michalski, V., Memisevic, R., Pal, C., & Vincent, P. (2017) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.206 · Cited by 80 · see citing works

Enable Scale and Aspect Ratio Adaptability in Visual Tracking with Detection Proposals

Huang, D., Luo, L., Wen, M., Chen, Z., & Zhang, C. (2015) · British Machine Vision Conference (BMVC) · doi:10.5244/c.29.185 · Cited by 73 · see citing works

Collaborative Correlation Tracking

Zhu, G., Wang, J., Wu, Y., & Lu, H. (2015) · British Machine Vision Conference (BMVC) · doi:10.5244/c.29.184 · Cited by 59 · see citing works

First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural NetworksPreprint

Gan, Q., Guo, Q., Zhang, Z., & Cho, K. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.06425 · Cited by 49 · see citing works

Tracking Randomly Moving Objects on Edge Box ProposalsPreprint

Zhu, G., Porikli, F., & Li, H. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1507.08085 · Cited by 43 · see citing works

Exploring Simple Siamese Representation Learning

Chen, X., & He, K. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01549 · Cited by 3,725 · see citing works

High Performance Visual Tracking with Siamese Region Proposal Network

Li, B., Yan, J., Wu, W., Zhu, Z., & Hu, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00935 · Cited by 3,023 · see citing works

ECO: Efficient Convolution Operators for Tracking

Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.733 · Cited by 2,805 · see citing works

ByteTrack: Multi-object Tracking by Associating Every Detection Box

Zhang, Y., Sun, P., Jiang, Y., Yu, D., Weng, F., Yuan, Z., Luo, P., Liu, W., & Wang, X. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_1 · Cited by 2,793 · see citing works

SiamRPN++: Evolution of Siamese Visual Tracking With Very Deep Networks

Li, B., Wu, W., Wang, Q., Zhang, F., Xing, J., & Yan, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00441 · Cited by 2,607 · see citing works

Deep Learning for 3D Point Clouds: A Survey

Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., & Bennamoun, M. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3005434 · Cited by 2,445 · see citing works

Fully Convolutional Siamese Networks for Change Detection

Daudt, R. C., Saux, B. L., & Boulch, A. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451652 · Cited by 1,872 · see citing works

GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild

Huang, L., Zhao, X., & Huang, K. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2957464 · Cited by 1,809 · see citing works

LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking

Fan, H., Lin, L., Yang, F., Chu, P., Deng, G., Yu, S., Bai, H., Xu, Y., Liao, C., & Ling, H. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00552 · Cited by 1,742 · see citing works

ATOM: Accurate Tracking by Overlap Maximization

Danelljan, M., Bhat, G., Khan, F. S., & Felsberg, M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00479 · Cited by 1,591 · see citing works

Transformer Tracking

Chen, X., Yan, B., Zhu, J., Wang, D., Yang, X., & Lu, H. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00803 · Cited by 1,588 · see citing works

Distractor-Aware Siamese Networks for Visual Object Tracking

Zhu, Z. D., Wang, Q., Li, B., Wu, W., Yan, J., & Hu, W. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01240-3_7 · Cited by 1,575 · see citing works

Fast Online Object Tracking and Segmentation: A Unifying Approach

Wang, Q., Zhang, L., Bertinetto, L., Hu, W., & Torr, P. H. S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00142 · Cited by 1,554 · see citing works

Learning Discriminative Model Prediction for Tracking

Bhat, G., Danelljan, M., Van Gool, L., & Timofte, R. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00628 · Cited by 1,515 · see citing works

Detection and tracking meet drones challenge

Zhu, P., Wen, L., Du, D., Bian, X., Fan, H., Hu, Q., & Ling, H. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3119563 · Cited by 1,336 · see citing works

Learning Spatio-Temporal Transformer for Visual Tracking

Yan, B., Peng, H., Fu, J., Wang, D., & Lu, H. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01028 · Cited by 1,280 · see citing works

Learning Background-Aware Correlation Filters for Visual Tracking

Galoogahi, H. K., Fagg, A., & Lucey, S. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.129 · Cited by 1,270 · see citing works

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

Müller, M., Bibi, A., Giancola, S., Alsubaihi, S., & Ghanem, B. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01246-5_19 · Cited by 1,192 · see citing works

Deeper and Wider Siamese Networks for Real-Time Visual Tracking

Zhang, Z., & Peng, H. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00472 · Cited by 1,160 · see citing works

Discriminative Correlation Filter with Channel and Spatial Reliability

Lukezic, A., Vojir, T., Zajc, L. C., Matas, J., & Kristan, M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.515 · Cited by 1,153 · see citing works

The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking

Du, D., Qi, Y., Yu, H., Yang, Y., Duan, K., Li, G., Zhang, W., Huang, Q., & Tian, Q. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01249-6_23 · Cited by 1,099 · see citing works

Siamese Box Adaptive Network for Visual Tracking

Chen, Z., Zhong, B., Li, G., Zhang, S., & Ji, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00670 · Cited by 1,052 · see citing works

SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking

Guo, D., Wang, J., Cui, Y., Wang, Z., & Chen, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00630 · Cited by 984 · see citing works

SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines

Xu, Y., Wang, Z., Li, Z., Yuan, Y., & Yu, G. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6944 · Cited by 974 · see citing works

Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking

Li, F., Tian, C., Zuo, W., Zhang, L., & Yang, M.-H. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00515 · Cited by 935 · see citing works

Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework

Ye, B., Chang, H., Ma, B., Shan, S., & Chen, X. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_20 · Cited by 930 · see citing works

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking

Wang, N., Zhou, W., Wang, J., & Li, H. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00162 · Cited by 913 · see citing works

Learning Dynamic Siamese Network for Visual Object Tracking

Guo, Q., Feng, W., Zhou, C., Huang, R., Wan, L., & Wang, S. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.196 · Cited by 904 · see citing works

Ocean: Object-Aware Anchor-Free Tracking

Zhang, Z., Peng, H., Fu, J., Li, B., & Hu, W. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58589-1_46 · Cited by 894 · see citing works

MixFormer: End-to-End Tracking with Iterative Mixed Attention

Cui, Y., Jiang, C., Wang, L., & Wu, G. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01324 · Cited by 890 · see citing works

Probabilistic Regression for Visual Tracking

Danelljan, M., Van Gool, L., & Timofte, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00721 · Cited by 798 · see citing works

Edge Computing for Autonomous Driving: Opportunities and Challenges

Liu, S., Liu, L., Tang, J., Yu, B., Wang, Y., & Shi, W. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2915983 · Cited by 778 · see citing works

A Twofold Siamese Network for Real-Time Object Tracking

He, A., Luo, C., Tian, X., & Zeng, W. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00508 · Cited by 708 · see citing works

The Visual Object Tracking VOT2016 Challenge Results

Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Cehovin, L., Vojír, T., Häger, G., Lukežič, A., Fernandez, G., et al. (2016) · ECCV Workshops · doi:10.1007/978-3-319-48881-3_54 · Cited by 776 · see citing works

Few-Shot Object Detection With Attention-RPN and Multi-Relation Detector

Fan, Q., Zhuo, W., Tang, C., & Tai, Y. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00407 · Cited by 680 · see citing works

Triplet Loss in Siamese Network for Object Tracking

Dong, X., & Shen, J. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01261-8_28 · Cited by 665 · see citing works

Large Margin Object Tracking with Circulant Feature Maps

Wang, M., Liu, Y., & Huang, Z. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.510 · Cited by 665 · see citing works

The Sixth Visual Object Tracking VOT2018 Challenge Results

Kristan, M., Leonardis, A., Matas, J., Felsberg, M., Pflugfelder, R., Zajc, L. Č., Vojír, T., Bhat, G., Lukežič, A., Eldesokey, A., et al. (2018) · ECCV Workshops · doi:10.1007/978-3-030-11009-3_1 · Cited by 805 · see citing works

Spiking Neural Networks and Their Applications: A Review

Yamazaki, K., Vo-Ho, V.-K., Bulsara, D., & Le, N. (2022) · Brain Sciences · doi:10.3390/brainsci12070863 · Cited by 653 · see citing works

TransTrack: Multiple Object Tracking with TransformerPreprint

Sun, P., Cao, J., Jiang, Y., Zhang, R., Xie, E., Yuan, Z., Wang, C., & Luo, P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.15460 · Cited by 640 · see citing works

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

Wang, Q., Teng, Z., Xing, J., Gao, J., Hu, W., & Maybank, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00510 · Cited by 604 · see citing works

Learning Video Object Segmentation from Static Images

Perazzi, F., Khoreva, A., Benenson, R., Schiele, B., & Sorkine‐Hornung, A. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.372 · Cited by 602 · see citing works

Detect to Track and Track to Detect

Feichtenhofer, C., Pinz, A., & Zisserman, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.330 · Cited by 595 · see citing works

VITAL: VIsual Tracking via Adversarial Learning

Song, Y., Ma, C., Wu, X., Gong, L., Bao, L., Zuo, W., Shen, C., Lau, R. W. H., & Yang, M. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00937 · Cited by 595 · see citing works

A review of object detection based on deep learning

Xiao, Y., Tian, Z., Yu, J., Zhang, Y., Liu, S., Du, S., & Lan, X. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08976-6 · Cited by 584 · see citing works

CREST: Convolutional Residual Learning for Visual Tracking

Song, Y., Ma, C., Gong, L., Zhang, J., Lau, R. W. H., & Yang, M. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.279 · Cited by 572 · see citing works

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

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SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

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Need for Speed: A Benchmark for Higher Frame Rate Object Tracking

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Graph Attention Tracking

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Deep visual tracking: Review and experimental comparison

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Unveiling the Power of Deep Tracking

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Video Instance Segmentation

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SeqTrack: Sequence to Sequence Learning for Visual Object Tracking

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Deformable Siamese Attention Networks for Visual Object Tracking

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Multi-cue Correlation Filters for Robust Visual Tracking

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Discriminative Correlation Filter Tracker with Channel and Spatial Reliability

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Target-Aware Deep Tracking

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Quasi-Dense Similarity Learning for Multiple Object Tracking

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Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking

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Learning the Model Update for Siamese Trackers

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The Seventh Visual Object Tracking VOT2019 Challenge Results

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Visual Tracking via Adaptive Spatially-Regularized Correlation Filters

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The Visual Object Tracking VOT2017 Challenge Results

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AutoTrack: Towards High-Performance Visual Tracking for UAV With Automatic Spatio-Temporal Regularization

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Unsupervised Deep Tracking

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Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking

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Multi-task Correlation Particle Filter for Robust Object Tracking

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Multitask learning for large-scale semantic change detection

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Deep Learning for Visual Tracking: A Comprehensive Survey

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Know Your Surroundings: Exploiting Scene Information for Object Tracking

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Graph Matching Networks for Learning the Similarity of Graph Structured ObjectsPreprint

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Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking

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STMTrack: Template-free Visual Tracking with Space-time Memory Networks

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AiATrack: Attention in Attention for Transformer Visual Tracking

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Learning feed-forward one-shot learnersPreprint

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Learning Target Candidate Association to Keep Track of What Not to Track

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Visual Prompt Multi-Modal Tracking

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Learning Dynamic Memory Networks for Object Tracking

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Autoregressive Visual Tracking

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SwinTrack: A Simple and Strong Baseline for Transformer Tracking

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LaSOT: A High-quality Large-scale Single Object Tracking Benchmark

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GradNet: Gradient-Guided Network for Visual Object Tracking

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Deep Affinity Network for Multiple Object Tracking

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Graph Convolutional Tracking

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HiFT: Hierarchical Feature Transformer for Aerial Tracking

Cao, Z., Fu, C., Ye, J., Li, B., & Li, Y. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01517 · Cited by 343 · see citing works

Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking

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Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking

Chen, B., Li, P., Bai, L., Qiao, L., Shen, Q., Li, B., Gan, W., Wu, W., & Ouyang, W. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_22 · Cited by 328 · see citing works

Vision-Based Anti-UAV Detection and Tracking

Zhao, J. W., Zhang, J., Li, D., & Wang, D. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3177627 · Cited by 330 · see citing works

End-to-End Flow Correlation Tracking with Spatial-Temporal Attention

Zhu, Z. D., Wu, W., Zou, W., & Yan, J. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00064 · Cited by 321 · see citing works

High-Performance Long-Term Tracking With Meta-Updater

Dai, K., Zhang, Y., Wang, D., Li, J., Lu, H., & Yang, X. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00633 · Cited by 310 · see citing works

Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline

Zhang, P., Zhao, J. W., Wang, D., Lu, H., & Ruan, X. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.00868 · Cited by 308 · see citing works

DCFNet: Discriminant Correlation Filters Network for Visual TrackingPreprint

Wang, Q., Gao, J. G., Xing, J., Zhang, M., & Hu, W. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.04057 · Cited by 305 · see citing works

Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark

Wang, X., Shu, X., Zhang, Z., Jiang, B., Wang, Y., Tian, Y., & Wu, F. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.01355 · Cited by 302 · see citing works

D3S – A Discriminative Single Shot Segmentation Tracker

Lukezic, A., Matas, J., & Kristan, M. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00716 · Cited by 300 · see citing works

Real-Time MDNet

Jung, I., Son, J., Baek, M., & Han, B. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01225-0_6 · Cited by 297 · see citing works

TCTrack: Temporal Contexts for Aerial Tracking

Cao, Z., Huang, Z., Pan, L., Zhang, S., Liu, Z., & Fu, C. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01438 · Cited by 296 · see citing works

Self-Supervised Deep Correlation Tracking

Yuan, D., Chang, X., Huang, P.-Y., Liu, Q., & He, Z. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3037518 · Cited by 288 · see citing works

Fast and Accurate Online Video Object Segmentation via Tracking Parts

Cheng, J., Tsai, Y., Hung, W.-C., Wang, S., & Yang, M. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00774 · Cited by 284 · see citing works

GlobalTrack: A Simple and Strong Baseline for Long-Term Tracking

Huang, L., Zhao, X., & Huang, K. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6758 · Cited by 279 · see citing works

Deep Feature Based Siamese Network for Visual Object Tracking

Lim, S.-C., Huh, J., & Kim, J.-C. (2022) · Energies · doi:10.3390/en15176388 · Cited by 3 · see citing works

Real-time object tracking based on improved fully-convolutional siamese network

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Template Update Based on 3D-Convolutional Siamese Network for Object Tracking

Lu, X., Wang, X., Wang, Z., & Hei, X. (2021) · Asia Conference on Computers and Communications (ACCC) · doi:10.1109/accc54619.2021.00016

Visual tracking using Siamese convolutional neural network with region proposal and domain specific updating

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Siamese Trackers Based on Deep Features for Visual Tracking

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