Fully-Convolutional Siamese Networks for Object Tracking

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380

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

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

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

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

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

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

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

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

Hierarchical Spatiotemporal Context-Aware Correlation Filters for Visual Tracking

Wang, W., Zhang, K., Lv, M., & Wang, J. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2964757 · Cited by 26

Visual Tracking by TridentAlign and Context Embedding

Choi, J., Kwon, J., & Lee, K. M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69532-3_31 · Cited by 26

A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems

Ussa, A., Rajen, C. S., Pulluri, T., Singla, D., Acharya, J., Chuanrong, G. F., Basu, A., & Ramesh, B. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3243679 · Cited by 26

DiTNet: End-to-End 3D Object Detection and Track ID Assignment in Spatio-Temporal World

Wang, S., Cai, P., Wang, L., & Liu, M. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3062016 · Cited by 27

Channel Graph Regularized Correlation Filters for Visual Object Tracking

Jain, M., Tyagi, A., Subramanyam, A. V., Denman, S., Sridharan, S., & Fookes, C. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3063144 · Cited by 26

Learning to Rank Proposals for Siamese Visual Tracking

Tang, F., & Ling, Q. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3120305 · Cited by 26

Water Target Recognition Method and Application for Unmanned Surface Vessels

Cheng, L., Deng, B., Yang, Y., Lyu, J., Zhao, J., Zhou, K., Yang, C., Wang, L., Yang, S., & He, Y. (2021) · IEEE Access · doi:10.1109/access.2021.3138983 · Cited by 26

Spatial–Spectral Cross-Correlation Embedded Dual-Transfer Network for Object Tracking Using Hyperspectral Videos

Lei, J., Liu, P., Xie, W., Gao, L., Li, Y., & Du, Q. (2022) · Remote Sensing · doi:10.3390/rs14153512 · Cited by 27

Detection of Glass Insulators Using Deep Neural Networks Based on Optical Imaging

Wang, J., Li, Y., & Chen, W.-X. (2022) · Remote Sensing · doi:10.3390/rs14205153 · Cited by 26

SiamTHN: Siamese Target Highlight Network for Visual Tracking

Bao, J., Chen, K., Sun, X., Zhao, L., Diao, W., & Yan, M. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3266485 · Cited by 27

NeighborTrack: Single Object Tracking by Bipartite Matching with Neighbor Tracklets and Its Applications to Sports

Chen, Y., Wang, C.-Y., Yang, C.-Y., Chang, H., Lin, Y.-L., Chuang, Y., & Liao, H.-Y. M. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00542 · Cited by 26

RTracker: Recoverable Tracking via PN Tree Structured Memory

Huang, Y., Li, X., Zhou, Z., Wang, Y., He, Z., & Yang, M. (2024) · 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/cvpr52733.2024.01801 · Cited by 26

Learning to Predict Pedestrian Intention via Variational Tracking Networks

Hoy, M., Tu, Z., Dang, K., & Dauwels, J. (2018) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2018.8569641 · Cited by 26

High speed long-term visual object tracking algorithm for real robot systems

Jiang, M., Li, R., Liu, Q., Shi, Y., & Tlelo‐Cuautle, E. (2021) · Neurocomputing · doi:10.1016/j.neucom.2020.12.113 · Cited by 26

TDIOT: Target-Driven Inference for Deep Video Object Tracking

Gürkan, F., Çerkezi, L., Cirakman, O., & Günsel, B. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3112010 · Cited by 27

Perspective-Adaptive Convolutions for Scene Parsing

Zhang, R., Tang, S., Zhang, Y., Li, J., & Yan, S. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2890637 · Cited by 25

Dual Attentional Siamese Network for Visual Tracking

Zhang, X., Ma, J., Liu, H., Hu, H., & Yang, P. (2022) · Displays · doi:10.1016/j.displa.2022.102205 · Cited by 26

A joint local–global search mechanism for long-term tracking with dynamic memory network

Gao, Z., Zhuang, Y., Gu, J., Yang, B., & Nie, Z. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119890 · Cited by 25

A Comprehensive Study of Object Tracking in Low-Light Environments

Yi, A., & Anantrasirichai, N. (2024) · Sensors · doi:10.3390/s24134359 · Cited by 25

RGB-T Tracking With Template-Bridged Search Interaction and Target-Preserved Template Updating

Li, B., Peng, F., Hui, T., Wei, X., Wei, X., Zhang, L., Shi, H., & Liu, S. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3475472 · Cited by 25

Consistencies are All You Need for Semi-supervised Vision-Language Tracking

Ge, J., Cao, J., Zhu, X., Zhang, X., Liu, C., Wang, K., & Liu, B. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3680657 · Cited by 27

Deep neural networks for data association in particle tracking

Yao, Y., Smal, I., & Meijering, E. H. W. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363615 · Cited by 25

High performance visual tracking with circular and structural operators

Gao, P., Ma, Y., Song, K., Li, C., Wang, F., Xiao, L., & Zhang, Y. (2018) · Knowledge-Based Systems · doi:10.1016/j.knosys.2018.08.008 · Cited by 25

Classification of Canker on Small Datasets Using Improved Deep Convolutional Generative Adversarial Networks

Zhang, M., Liu, S., Yang, F., & Liu, J. (2019) · IEEE Access · doi:10.1109/access.2019.2900327 · Cited by 25

Toward Intelligent Surveillance as an Edge Network Service (iSENSE) Using Lightweight Detection and Tracking Algorithms

Nikouei, S. Y., Chen, Y., Song, S., Choi, B., & Faughnan, T. R. (2019) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2019.2916416 · Cited by 25

Dense Contour-Imbalance Aware framework for Colon Gland Instance Segmentation

Mei, L., Guo, X., Huang, X., Weng, Y., Liu, S., & Lei, C. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101988 · Cited by 25

A Real-time Robust Approach for Tracking UAVs in Infrared Videos

Wu, H., Li, W., Li, W., & Liu, G. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00524 · Cited by 25

Convolutional Neural Networks for individual identification in the Southern Rock Lobster supply chain

Vo, S. A., Scanlan, J. D., Turner, P. A., & Ollington, R. (2020) · Food Control · doi:10.1016/j.foodcont.2020.107419 · Cited by 26

Tracking-by-Trackers with a Distilled and Reinforced Model

Dunnhofer, M., Martinel, N., & Micheloni, C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69532-3_38 · Cited by 25

Antidecay LSTM for Siamese Tracking With Adversarial Learning

Zhao, F., Zhang, T., Wu, Y., Tang, M., & Wang, J. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3018025 · Cited by 25

Composite deep learning framework for absolute 3D shape measurement based on single fringe phase retrieval and speckle correlation

Yin, W., Zhong, J., Feng, S., Tao, T., Han, J., Huang, L., Chen, Q., & Zuo, C. (2020) · Journal of Physics Photonics · doi:10.1088/2515-7647/abbcd9 · Cited by 26

Learning Recurrent Memory Activation Networks for Visual Tracking

Pu, S., Song, Y., Ma, C., Zhang, H., & Yang, M. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3038356 · Cited by 25

A Visual Tracking System for Honey Bee (Hymenoptera: Apidae) 3D Flight Trajectory Reconstruction and Analysis

Sun, C., & Gaydecki, P. A. (2021) · Journal of Insect Science · doi:10.1093/jisesa/ieab023 · Cited by 25

IQMA Network: Image Quality Multi-scale Assessment Network

Guo, H., Bin, Y., Hou, Y., Zhang, Q., & Luo, H. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00055 · Cited by 26

Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency

Wu, H., & Wang, X. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00999 · Cited by 26

Two-stage aware attentional Siamese network for visual tracking

Sun, X., Han, G., Guo, L., Yang, H., Wu, X., & Li, Q. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108502 · Cited by 27

A Survey on Symmetrical Neural Network Architectures and Applications

Ilina, O. V., Ziyadinov, V., Klenov, N. V., & Tereshonok, M. V. (2022) · Symmetry · doi:10.3390/sym14071391 · Cited by 27

Exploiting More Information in Sparse Point Cloud for 3D Single Object Tracking

Cui, Y., Shan, J., Gu, Z., Li, Z., & Fang, Z. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3208687 · Cited by 25

A UAV to UAV tracking benchmark

Wang, Y., Huang, Z., Laganière, R., Zhang, H., & Ding, L. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110197 · Cited by 25

Learning spatial variance-key surrounding-aware tracking via multi-expert deep feature fusion

Elayaperumal, D., & Joo, Y. H. (2023) · Information Sciences · doi:10.1016/j.ins.2023.02.009 · Cited by 25

SiamCAF: Complementary Attention Fusion-Based Siamese Network for RGBT Tracking

Xue, Y., Zhang, J., Lin, Z., Li, C., Huo, B., & Zhang, Y. (2023) · Remote Sensing · doi:10.3390/rs15133252 · Cited by 25

MTNet: Learning Modality-aware Representation with Transformer for RGBT Tracking

Hou, R., Boyue, X., Ren, T., & Wu, G. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00203 · Cited by 25

Region Selective Fusion Network for Robust RGB-T Tracking

Yu, Z., Fan, H., Wang, Q., Li, Z., & Tang, Y. (2023) · IEEE Signal Processing Letters · doi:10.1109/lsp.2023.3316021 · Cited by 25

PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework

Li, B., Huang, Z., Ye, J., Li, Y., Scherer, S., Zhao, H., & Fu, C. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00918 · Cited by 29

A robust visual tracking method via local feature extraction and saliency detection

Wang, Y., Wei, X., Ding, L., Tang, X., & Zhang, H. (2019) · The Visual Computer · doi:10.1007/s00371-019-01646-1 · Cited by 25

Robust Long-Term Tracking via Instance-Specific Proposals

Liu, H., Hu, Q., Li, B., & Guo, Y. (2019) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2019.2908715 · Cited by 25

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

VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results

Fan, H., Wen, L., Du, D., Zhu, P., Hu, Q., Ling, H., Shah, M. A., Wang, B., Dong, B., Yuan, D., et al. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-66823-5_44 · Cited by 26

Light-weight UAV object tracking network based on strategy gradient and attention mechanism

Hua, X., Wang, X., Rui, T., Shao, F., & Wang, D. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107071 · Cited by 25

Efficient object tracking using hierarchical convolutional features model and correlation filters

Abbass, M. Y., Kwon, K.-C., Kim, N., Abdelwahab, S. A., El-Samie, F. E. A., & Khalaf, A. A. M. (2021) · The Visual Computer · doi:10.1007/s00371-020-01833-5 · Cited by 24

Few-shot learning based histopathological image classification of colorectal cancer

Li, R., Li, X., Sun, H., Yang, J., Rahaman, M. M., Grzegozek, M., Jiang, T., Huang, X., & Li, C. (2024) · Intelligent Medicine · doi:10.1016/j.imed.2024.05.003 · Cited by 24

Unifying Motion and Appearance Cues for Visual Tracking via Shared Queries

Xue, C., Zhong, B., Liang, Q., Xia, H., & Song, S. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3486347 · Cited by 25

NiDR: Nighttime Aerial Tracking via Decoupled Representations

Xu, L., Zhang, Y., Xu, C., Cheng, W., & Yang, W. T. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3508136 · Cited by 25

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

MeMu: Metric correlation Siamese network and multi-class negative sampling for visual tracking

Xiao, Y., Li, J., Du, B., Wu, J. X., Chang, J., & Zhang, W. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107170 · Cited by 25

ST-VIO: Visual Inertial Odometry Combined with Image Segmentation and Tracking

Zhang, C., Chen, L., & Yuan, S. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.2989877 · Cited by 24

Distractor-aware discrimination learning for online multiple object tracking

Zhou, Z., Luo, W., Wang, Q., Xing, J., & Hu, W. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107512 · Cited by 24

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

AVOT: Audio-Visual Object Tracking of Multiple Objects for Robotics

Wilson, J., & Lin, M. C. (2020) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra40945.2020.9197528 · Cited by 24

Deep Learning Based Motion Tracking of Ultrasound Image Sequences

Bharadwaj, S. S., & Almekkawy, M. K. (2020) · IEEE International Ultrasonics Symposium · doi:10.1109/ius46767.2020.9251739 · Cited by 24

TSDM: Tracking by SiamRPN++ with a Depth-refiner and a Mask-generator

Pengyao, Z., Liu, Q., Wang, W., & Guo, Q. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413315 · Cited by 24

High-performance UAVs visual tracking based on siamese network

Yang, S., Chen, H., Xu, F., Li, Y., & Yuan, J. (2021) · The Visual Computer · doi:10.1007/s00371-021-02271-7 · Cited by 24

A Time Sequence Images Matching Method Based on the Siamese Network

Tao, B., Huang, L., Zhao, H., Li, G., & Tong, X. (2021) · Sensors · doi:10.3390/s21175900 · Cited by 24

Hierarchical Convolution Fusion-Based Adaptive Siamese Network for Infrared Target Tracking

Xu, Y., Wan, M., Chen, Q., Qian, W., Ren, K., & Gu, G. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3117052 · Cited by 24

Siamese Cross-Domain Tracker Design for Seamless Tracking of Targets in RGB and Thermal Videos

Chandrakanth, V., Murthy, V. S. N., & Channappayya, S. S. (2022) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2022.3151307 · Cited by 24

Combining complementary trackers for enhanced long-term visual object tracking

Dunnhofer, M., Simonato, K., & Micheloni, C. (2022) · Image and Vision Computing · doi:10.1016/j.imavis.2022.104448 · Cited by 24

GFSNet: Generalization-friendly siamese network for thermal infrared object tracking

Chen, R., Liu, S., Miao, Z., & Li, F. (2022) · Infrared Physics & Technology · doi:10.1016/j.infrared.2022.104190 · Cited by 24

Vehicle Tracking on Satellite Video Based on Historical Model

Chen, S., Wang, T., Wang, H., Wang, Y., Hong, J., Dong, T., & Li, Z. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3195522 · Cited by 24

Fusion of Multidimensional CNN and Handcrafted Features for Small-Sample Hyperspectral Image Classification

Tang, H., Li, Y., Huang, Z., Zhang, L., & Xie, W. (2022) · Remote Sensing · doi:10.3390/rs14153796 · Cited by 24

Study on intelligent and visualization method of ultrasonic testing of composite materials based on deep learning

Hu, Q., Wei, X., Guo, H., Xu, H., Li, C., He, W., & Pei, B. (2023) · Applied Acoustics · doi:10.1016/j.apacoust.2023.109363 · Cited by 24

Robust Drogue Positioning System Based on Detection and Tracking for Autonomous Aerial Refueling of UAVs

Tong, K. W., Wu, J., & Hou, Y. (2023) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2023.3308230 · Cited by 24

Enhanced Target Tracking Algorithm for Autonomous Driving Based on Visible and Infrared Image Fusion

Yuan, Q., Shi, H., Xuan, A. T. Y., Gao, M., Xu, Q., & Wang, J. (2023) · Journal of Intelligent and Connected Vehicles · doi:10.26599/jicv.2023.9210018 · Cited by 24

Mixed Traffic Trajectory Prediction Using LSTM–Based Models in Shared Space

Cheng, H., & Sester, M. (2018) · Lecture notes in geoinformation and cartography · doi:10.1007/978-3-319-78208-9_16 · Cited by 24

An adaptive template matching-based single object tracking algorithm with parallel acceleration

Yan, B., Xiao, L., Zhang, H., Xu, D., Ruan, L., Wang, Z., & Zhang, Y. (2019) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2019.102603 · Cited by 24

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

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

Residual Attention SiameseRPN for Visual Tracking

Cheng, X., Li, E., & Fu, Z. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60639-8_34 · Cited by 24

A new deep learning method for displacement tracking from ultrasound RF signals of vascular walls

Xiao, C., Li, Z.-Z., Lü, J., Wang, J., Zheng, H., Bi, Z., Chen, M., Mao, R., & Lu, M. (2020) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2020.101819 · Cited by 24

Dynamic PET Image Denoising With Deep Learning-Based Joint Filtering

He, Y., Cao, S., Zhang, H., Sun, H., Wang, F., Zhu, H., Lv, W., & Lu, L. (2021) · IEEE Access · doi:10.1109/access.2021.3064926 · Cited by 24

An In-Depth Analysis of Visual Tracking with Siamese Neural NetworksPreprint

Pflugfelder, R. P. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.00569 · Cited by 29

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

OS-FPI: A Coarse-to-Fine One-Stream Network for UAV Geolocalization

Chen, J., Zheng, E., Dai, M. J., Chen, Y., & Lu, Y. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3380902 · Cited by 23

Memristor-Based Attention Network for Online Real-Time Object Tracking

Deng, Z., Wang, C., Lin, H., Deng, Q., & Sun, Y. (2024) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2024.3437345 · Cited by 23

A Survey of Few-Shot Learning for Biomedical Time Series

Li, C., Denison, T., & Zhu, T. (2024) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2024.3492381 · Cited by 26

HotMoE: Exploring Sparse Mixture-of-Experts for Hyperspectral Object Tracking

Sun, W., Tan, Y., Li, J., Hou, S., Li, X., Shao, Y., Wang, Z., & Song, B. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3535339 · 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

A Model Based on Siamese Neural Network for Online Transaction Fraud Detection

Zhou, X., Zhang, Z., Wang, L., & Wang, P. (2019) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8852295 · Cited by 24

Object Tracking Using Spatio-Temporal Networks for Future Prediction Location

Liu, Y., Li, R., Cheng, Y., Tan, R. T., & Sui, X. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58542-6_1 · Cited by 23

Deep Template-based Object Instance Detection

Mercier, J.-P., Garon, M., Giguère, P., & Lalonde, J. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00155 · Cited by 25

Twin neural network regression

Wetzel, S. J., Ryczko, K., Melko, R. G., & Tamblyn, I. (2022) · Applied AI Letters · doi:10.1002/ail2.78 · Cited by 24

Feature Aggregation Networks Based on Dual Attention Capsules for Visual Object Tracking

Cao, Y., Ji, H., Zhang, W., & Shirani, S. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3063001 · Cited by 23

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

Multiple Pedestrians and Vehicles Tracking in Aerial Imagery Using a Convolutional Neural Network

Azimi, S. M., Kraus, M., Bahmanyar, R., & Reinartz, P. H. (2021) · Remote Sensing · doi:10.3390/rs13101953 · Cited by 23

Query-Memory Re-Aggregation for Weakly-supervised Video Object Segmentation

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