Online Object Tracking: A Benchmark

Histograms of Oriented Gradients for Human Detection

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Robust Real-Time Face Detection

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Object tracking

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CONDENSATION—Conditional Density Propagation for Visual Tracking

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Kernel-based object tracking

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Lucas-Kanade 20 Years On: A Unifying Framework

Baker, S., & Matthews, I. A. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000011205.11775.fd · Cited by 3,159

Incremental Learning for Robust Visual Tracking

Ross, D. A., Lim, J., Lin, R.-S., & Yang, M.-H. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0075-7 · Cited by 3,061

Learning to detect natural image boundaries using local brightness, color, and texture cues

Martin, D. R., Fowlkes, C. C., & Malik, J. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.1273918 · Cited by 2,457

Description-Discrimination Collaborative Tracking

Chen, D., Yuan, Z., Hua, G., Wu, Y., & Zheng, N. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10590-1_23 · Cited by 22

Target tracking with dynamically adaptive correlation

Gaxiola, L. N., Diaz-Ramirez, V. H., Tapia, J. J., & Garcı́a-Martı́nez, P. (2015) · Optics Communications · doi:10.1016/j.optcom.2015.11.077 · Cited by 24

Robust tracking via monocular active vision for an intelligent teaching system

Wang, R., Dong, H., Han, T. X., & Mei, L. (2016) · The Visual Computer · doi:10.1007/s00371-015-1206-8 · Cited by 24

Human Upper Limb Motion Analysis for Post-Stroke Impairment Assessment Using Video Analytics

Yang, C., Kerr, A., Stanković, V., Stanković, L., Rowe, P. J., & Cheng, S. S. M. (2016) · IEEE Access · doi:10.1109/access.2016.2523803 · Cited by 23

Interactive motion effects design for a moving object in 4D films

Lee, J., Han, B., & Choi, S. (2016) · ACM Symposium on Virtual Reality Software and Technology (VRST) · doi:10.1145/2993369.2993389 · Cited by 24

Multi-Task Structure-Aware Context Modeling for Robust Keypoint-Based Object Tracking

Li, X., Zhao, L.-M., Ji, W., Wu, Y., Wu, F. Q., Yang, M., Tao, D., & Reid, I. D. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2818132 · Cited by 24

Channel Pruning for Visual Tracking

Che, M., Wang, R., Lu, Y., Li, Y., Zhi, H., & Xiong, C. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-11009-3_3 · Cited by 23

An Integrated Deep Learning Framework for Occluded Pedestrian Tracking

Chen, K., Song, X., Zhai, X., Zhang, B., Hou, B., & Wang, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2900296 · Cited by 24

Online Object Tracking, Learning and Parsing with And-Or Graphs

Wu, T., Lu, Y., & Zhu, S. C. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2644963 · Cited by 25

Robust Visual Tracking based on Adversarial Unlabeled Instance Generation with Label Smoothing Loss Regularization

Han, Y., Zhang, P., Huang, W., Zha, Y., Cooper, G. D., & Zhang, Y. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107027 · Cited by 24

Object-adaptive LSTM network for real-time visual tracking with adversarial data augmentation

Du, Y., Yan, Y., Chen, S., & Yang, H. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.12.022 · Cited by 24

Three-step action search networks with deep Q-learning for real-time object tracking

Teng, Z., Zhang, B., & Jianping Fan, B. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2019.107188 · Cited by 25

Object Tracking in Unmanned Aerial Vehicle Videos via Multifeature Discrimination and Instance-Aware Attention Network

Zhang, S., Li, Z., Zhang, H., & Li, J. (2020) · Remote Sensing · doi:10.3390/rs12162646 · Cited by 24

3D Siamese Voxel-to-BEV Tracker for Sparse Point CloudsPreprint

Hui, L., Wang, L., Cheng, M., Xie, J., & Yang, J. J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.04426 · Cited by 28

An equalised global graphical model-based approach for multi-camera object trackingPreprint

Chen, W., Cao, L., Chen, X., & Huang, K. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.03532 · Cited by 24

Robust 3D tracking of unknown objects

Pieropan, A., Bergström, N., Ishikawa, M., & Kjellström, H. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139520 · Cited by 23

Visual Tracking via Sparse and Local Linear Coding

Wang, G., Qin, X., Zhong, F., Liu, Y., Li, H., Peng, Q., & Yang, M. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2445291 · Cited by 23

Visual Tracking by Sampling Tree-Structured Graphical Models

Hong, S., & Han, B. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10590-1_1 · Cited by 23

Robust Visual Tracking Using Exemplar-Based Detectors

Gao, C., Chen, F., Yu, J.-G., Huang, R., & Sang, N. (2015) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2513700 · Cited by 23

Beyond Standard Benchmarks: Parameterizing Performance Evaluation in Visual Object Tracking

Zajc, L. Č., Lukežič, A., Leonardis, A., & Kristan, M. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.360 · Cited by 23

Visual object tracking with online sample selection via lasso regularization

Liu, Q., Ma, X., Ou, W., & Zhou, Q. (2017) · Signal Image and Video Processing · doi:10.1007/s11760-016-1035-x · Cited by 23

Parallel Attentive Correlation Tracking

Zhang, K., Fan, J., Liu, Q., Yang, J. J., & Lian, W. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2868561 · Cited by 24

Visual tracking with online structural similarity-based weighted multiple instance learning

Fu, C., Duan, R., & Kayacan, E. (2019) · Information Sciences · doi:10.1016/j.ins.2018.12.080 · Cited by 23

EnKCF: Ensemble of Kernelized Correlation Filters for High-Speed Object Tracking

Uzkent, B., & Seo, Y. (2018) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2018.00129 · Cited by 23

Dual-regression model for visual tracking

Li, X., Liu, Q., Fan, N., Zhou, Z., He, Z., & Jing, X. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.09.011 · Cited by 24

NoisyOTNet: A Robust Real-Time Vehicle Tracking Model for Traffic Surveillance

Xing, W., Yang, Y., Zhang, S., Yu, Q., & Wang, L. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3086104 · Cited by 23

Visual Object Detection and Tracking for Internet of Things Devices Based on Spatial Attention Powered Multidomain Network

Gao, H., Yu, L., Khan, I. A., Wang, Y., Yang, Y., & Shen, H. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3099855 · Cited by 23

Target-Distractor Aware Deep Tracking With Discriminative Enhancement Learning Loss

Zhang, H., Cheng, L., Zhang, T., Wang, Y., Zhang, W., & Zhang, J. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3165536 · Cited by 23

Robust Object Tracking via Locality Sensitive Histograms

He, S., Lau, R. W. H., Yang, Q., Wang, J., & Yang, M. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2527300 · Cited by 23

Multiple player tracking in soccer videos: an adaptive multiscale sampling approach

Kim, W., Moon, S.-W., Lee, J., Nam, D.-W., & Jung, C. (2018) · Multimedia Systems · doi:10.1007/s00530-018-0586-9 · Cited by 23

Intra-Frame Object Tracking by Deblatting

Kotera, J., Rozumnyi, D., Šroubek, F., & Matas, J. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00283 · Cited by 23

Joint Channel Reliability and Correlation Filters Learning for Visual Tracking

Du, F., Liu, P., Zhao, W., & Tang, X. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2909654 · Cited by 23

Location-Aware and Regularization-Adaptive Correlation Filters for Robust Visual Tracking

Liu, R., Chen, Q., Yao, Y., Fan, X., & Luo, Z. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3005447 · Cited by 23

Visual Object Tracking in Drone Images with Deep Reinforcement Learning

Gozen, D., & Özer, S. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413316 · Cited by 23

An overview of object detection and tracking

Zhao, Y., Shi, H., Chen, X., Li, X., & Wang, C. (2015) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2015.7279299 · Cited by 23

Similarity Mapping with Enhanced Siamese Network for Multi-Object TrackingPreprint

Kim, M., Alletto, S., & Rigazio, L. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.09156 · Cited by 30

Online learning for the hyoid bone tracking during swallowing with neck movement adjustment using semantic segmentation

Lee, D., Lee, W. H., Seo, H. G., Oh, B.-M., Lee, J. C., & Kim, H. C. (2020) · IEEE Access · doi:10.1109/access.2020.3019532 · Cited by 22

A temporal sparse collaborative appearance model for visual tracking

Zhao, J., Chen, N., & Zhou, Z. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08630-1 · Cited by 22

WATB: Wild Animal Tracking Benchmark

Wang, F., Ping, C., Li, F., Wang, X., He, B., & Sun, F. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01732-3 · Cited by 22

Lightweight full-convolutional siamese tracker

Li, Y., Wang, B., Wu, X., Liu, Z., & Li, Y. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111439 · Cited by 27

UAV target tracking: a survey

Wu, P., Li, Y., & Dong, X. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11348-x · Cited by 29

Pyramid-Based Visual Tracking Using Sparsity Represented Mean Transform

Zhang, Z., & Wong, K. H. (2014) · 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.2014.160 · Cited by 22

Exploiting Spatial Structure from Parts for Adaptive Kernelized Correlation Filter Tracker

Yao, R., Xia, S., Shen, F., Zhou, Y. Z., & Niu, Q. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2545705 · Cited by 22

Multi-feature tracking via adaptive weights

Jiang, H., Li, J., Wang, D., & Lu, H. (2016) · Neurocomputing · doi:10.1016/j.neucom.2016.03.074 · Cited by 22

Detection of complex video events through visual rhythm

Torres, B. S., & Pedrini, H. (2016) · The Visual Computer · doi:10.1007/s00371-016-1321-1 · Cited by 22

Feature Distilled Tracking

Zhu, G., Wang, J., Wang, P., Wu, Y., & Lu, H. (2017) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2017.2776977 · Cited by 21

Visual object tracking with multi-scale superpixels and color-feature guided kernelized correlation filters

Wang, J., Liu, W., Xing, W., & Zhang, S. (2018) · Signal Processing Image Communication · doi:10.1016/j.image.2018.01.005 · Cited by 22

Adaptive feature representation for visual tracking

Han, Y., Deng, C., Zhang, Z., Li, J., & Zhao, B. (2017) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2017.8296605 · Cited by 22

Adaptive Compressive Tracking via Online Vector Boosting Feature Selection

Liu, Q., Yang, J., Zhang, K., & Wu, Y. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2016.2606512 · Cited by 22

Intelligent Framework for Worker-Machine Safety Assessment

Hu, Q., Bai, Y., He, L., Cai, Q., Tang, S., Ma, G., Tan, J., & Liang, B. (2020) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001801 · Cited by 22

Robust adaptive learning with Siamese network architecture for visual tracking

Zhang, W., Du, Y., Chen, Z., Deng, J., & Liu, P. (2020) · The Visual Computer · doi:10.1007/s00371-020-01839-z · Cited by 22

A KCF-Based Incremental Target Tracking Method With Constant Update Speed

Zhao, F., Hui, K., Wang, T., Zhang, Z., & Chen, Y. (2021) · IEEE Access · doi:10.1109/access.2021.3080308 · Cited by 23

Is First Person Vision Challenging for Object Tracking?

Dunnhofer, M., Furnari, A., Farinella, G. M., & Micheloni, C. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00304 · Cited by 24

FPGA implementation of multi-dimensional Kalman filter for object tracking and motion detection

Babu, P., & Parthasarathy, E. (2021) · Engineering Science and Technology an International Journal · doi:10.1016/j.jestch.2021.101084 · Cited by 22

Adaptive temporal feature modeling for visual tracking via cross-channel learning

Wang, Y., Zhang, W., Lai, C., & Wang, J. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110380 · Cited by 23

A Universal Event-Based Plug-In Module for Visual Object Tracking in Degraded Conditions

Zhang, J., Dong, B., Fu, Y., Wang, Y., Wei, X., Yin, B., & Yang, X. S. (2023) · International Journal of Computer Vision · doi:10.1007/s11263-023-01959-8 · Cited by 22

Multi-Scale Enhanced Features Correlation Filters Learning With Dual Second-Order Difference for UAV Tracking

Yu, Y., Zhang, Y., Chen, L., Ge, P., & Chen, C. L. P. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3355171 · Cited by 23

Part-Based Robust Tracking Using Online Latent Structured Learning

Yao, R., Shi, Q., Shen, C., Zhang, Y., & van den Hengel, A. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2527358 · Cited by 19

Adaptive low-rank subspace learning with online optimization for robust visual tracking

Liu, R., Wang, D., Han, Y., Fan, X. N., & Luo, Z. (2017) · Neural Networks · doi:10.1016/j.neunet.2017.02.002 · Cited by 22

Super-Resolved Fine-Scale Sea Ice Motion Tracking

Xian, Y., Petrou, Z. I., Tian, Y., & Meier, W. N. (2017) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2017.2699081 · Cited by 22

Visual Tracking via Subspace Learning: A Discriminative Approach

Sui, Y., Tang, Y., Zhang, L., & Wang, G. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-017-1049-z · Cited by 22

Robust template matching using scale-adaptive deep convolutional features

Kim, J., Kim, J., Choi, S., Hasan, M. A., & Kim, C. (2017) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipa.2017.8282124 · Cited by 22

Correlation filter‐based visual tracking via adaptive weighted CNN features fusion

Hao, Z., Liu, G., & Zhang, H. (2018) · IET Image Processing · doi:10.1049/iet-ipr.2017.0443 · Cited by 22

Reliable correlation tracking via dual-memory selection model

Li, G., Peng, M., Nai, K., Li, Z., & Li, K. (2020) · Information Sciences · doi:10.1016/j.ins.2020.01.015 · Cited by 22

DART: Distribution Aware Retinal Transform for Event-based CamerasPreprint

Ramesh, B., Yang, H., Orchard, G., Thi, N. A. L., Zhang, S., & Xiang, C. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1710.10800 · Cited by 24

PAC Confidence Sets for Deep Neural Networks via Calibrated PredictionPreprint

Park, S., Bastani, O., Matni, N., & Lee, I. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.00106 · Cited by 25

CRTrack: Learning Correlation-Refine network for visual object tracking

Zhang, W., Xie, F., Xu, T., Zhai, J., & Yang, W. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110582 · Cited by 21

MambaEVT: Event Stream-Based Visual Object Tracking Using State Space Model

Wang, X., Wang, C., Wang, S., Wang, X., Zhao, Z., Zhu, L., & Jiang, B. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3588533 · Cited by 21

Collaborative object tracking model with local sparse representation

Xie, C., Tan, J., Chen, P., Zhang, J., & He, L. (2013) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2013.12.012 · Cited by 21

Object tracking based on an online learning network with total error rate minimization

Jang, S.-I., Choi, K., Toh, K., Teoh, A. B. J., & Kim, J. (2014) · Pattern Recognition · doi:10.1016/j.patcog.2014.07.020 · Cited by 21

Top–down visual attention integrated particle filter for robust object tracking

Li, W., Wang, P., & Qiao, H. (2016) · Signal Processing Image Communication · doi:10.1016/j.image.2016.01.001 · Cited by 21

Multi-Tracker Partition Fusion

Khalid, O., SanMiguel, J. C., & Cavallaro, A. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2016.2542699 · Cited by 21

Locality-Constrained Collaborative Model for Robust Visual Tracking

Zhou, T., Lu, Y., & Di, H. (2015) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2493498 · Cited by 21

Contextual Bag-of-Words for Robust Visual Tracking

Zeng, F., Ji, Y., & Levine, M. D. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2778561 · Cited by 22

Robust Structural Low-Rank Tracking

Javed, S., Mahmood, A., Dias, J. M. M., & Werghi, N. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.2972102 · Cited by 21

Dissected 3D CNNs: Temporal skip connections for efficient online video processing

Köpüklü, O., Hörmann, S., Herzog, F., Çevıkalp, H., & Rigoll, G. (2021) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2021.103318 · Cited by 23

Part-Based Object Tracking Using Multiple Adaptive Correlation Filters

Barcellos, P., & Scharcanski, J. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3088455 · Cited by 21

Residual memory inference network for regression tracking with weighted gradient harmonized loss

Zhang, H., Zhang, J., Nie, G., Hu, J., & Zhang, W. (2022) · Information Sciences · doi:10.1016/j.ins.2022.03.047 · Cited by 22

Improved Kernel Correlation Filter Based Moving Target Tracking for Robot Grasping

Peng, F., Xu, Q., Li, Y., Zheng, M., & Su, H. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3195258 · Cited by 21

Vision-based drone control for autonomous UAV cinematography

Mademlis, I., Symeonidis, C., Tefas, A., & Pitas, I. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15336-7 · Cited by 20

Robust Correlation Filter Learning With Continuously Weighted Dynamic Response for UAV Visual Tracking

Zhang, Y., Yu, Y., Chen, L., & Ding, W. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3325337 · Cited by 22

Learning deep features for multiple object tracking by using a multi-task learning strategy

Wang, L., Pham, N. T., Ng, T.-T., Wang, G., Chan, K. L., & Leman, K. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025168 · Cited by 22

Patch-based Scale Calculation for Real-time Visual Tracking

Xu, Y., Wang, J., Li, H., Li, Y., Miao, Z., & Zhang, Y. (2015) · IEEE Signal Processing Letters · doi:10.1109/lsp.2015.2479360 · Cited by 21

Thermal Tracking of Sports Players

Gade, R., & Moeslund, T. B. (2014) · Sensors · doi:10.3390/s140813679 · Cited by 21

Deformable object tracking with spatiotemporal segmentation in big vision surveillance

Zhang, P., Zhuo, T., Xie, L., & Zhang, Y. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.07.149 · Cited by 21

Robust Object Tracking by Nonlinear Learning

Ma, B., Hu, H., Shen, J., Zhang, Y., Shao, L., & Porikli, F. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2776124 · Cited by 21

Using fuzzy least squares support vector machine with metric learning for object tracking

Zhang, S., Lu, W. B., Xing, W., & Zhang, L. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.07.012 · Cited by 20

Robust visual tracking via nonlocal regularized multi-view sparse representation

Kang, B., Zhu, W., Liang, D., & Chen, M. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.11.005 · Cited by 21

Real-Time Deep Tracking via Corrective Domain Adaptation

Li, H., Wang, X., Shen, F., Li, Y., Porikli, F., & Wang, M. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2923639 · Cited by 21

Long-term correlation tracking using multi-layer hybrid features in sparse and dense environments

Baisa, N. L., Bhowmik, D., & Wallace, A. M. (2018) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2018.06.027 · Cited by 2

Hybridizing Teaching-Learning-Based Optimization With Adaptive Grasshopper Optimization Algorithm for Abrupt Motion Tracking

Zhang, H., Gao, Z., Ma, X., Zhang, J., & Zhang, J. (2019) · IEEE Access · doi:10.1109/access.2019.2954500 · Cited by 21

Visual Object Tracking Via Multi-Stream Deep Similarity Learning Networks

Li, K., Kong, Y., & Fu, Y. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2959249 · Cited by 21

Advances in Deep Learning Methods for Visual Tracking: Literature Review and Fundamentals

Zhang, X., Jiang, R.-H., Fan, C., Tong, T.-Y., Wang, T., & Huang, P. (2021) · Machine Intelligence Research · doi:10.1007/s11633-020-1274-8 · Cited by 22

Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition ApplicationsPreprint

Roffo, G. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.05933 · Cited by 30

Motion-Aware Correlation Filters for Online Visual Tracking

Zhang, Y., Yang, Y., Zhou, W., Shi, L., & Li, D. (2018) · Sensors · doi:10.3390/s18113937 · Cited by 20

An efficient similarity-based level set model for medical image segmentation

Yu, H., He, F., Pan, Y., & Chen, X. (2016) · Journal of Advanced Mechanical Design Systems and Manufacturing · doi:10.1299/jamdsm.2016jamdsm0100 · Cited by 20

Spatial windowing for correlation filter based visual tracking

Gündoğdu, E., & Alatan, A. A. (2016) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2016.7532645 · Cited by 20

Multi-Stream Deep Similarity Learning Networks for Visual Tracking

Li, K., Kong, Y., & Fu, Y. (2017) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/301 · Cited by 20

Exploiting Spatial-Temporal Locality of Tracking via Structured Dictionary Learning

Sui, Y., Wang, G., Zhang, L., & Yang, M. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2779275 · Cited by 19

Efficient Tracking of Moving Target Based on an Improved Fast Differential Evolution Algorithm

Lin, L., & Zhu, M. (2018) · IEEE Access · doi:10.1109/access.2018.2793298 · Cited by 21

Object Tracking Benchmark

Wu, Y., Lim, J., & Yang, M.-H. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2388226 · Cited by 3,371

An experimental comparison of online object-tracking algorithms

Wang, Q., Chen, F., Xu, W., & Yang, M. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.895965 · Cited by 69

Visual object tracking: A survey

Chen, F., Wang, X., Zhao, Y., Lv, S., & Niu, X. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103508 · Cited by 159

Visual Object Tracking Using Deep Learning Techniques: A Comparison

Su, E. (2024) · Transactions on Computer Science and Intelligent Systems Research · doi:10.62051/7wag7n50 · Cited by 1

Single Object Trackers in OpenCV: A Benchmark

Brdjanin, A., Dardagan, N., Džigal, D., & Akagić, A. (2020) · International Conference on Innovations in Intelligent Systems and Applications (INISTA) · doi:10.1109/inista49547.2020.9194647 · Cited by 31