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

Toward Accurate Pixelwise Object Tracking via Attention Retrieval

Zhang, Z., Liu, Y., Li, B., Hu, W., & Peng, H. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3117077 · Cited by 31

SSET: a dataset for shot segmentation, event detection, player tracking in soccer videos

Feng, N., Song, Z., Yu, J., Chen, Y. P., Zhao, Y., He, Y., & Guan, T. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09414-3 · Cited by 37

COMET: Context-Aware IoU-Guided Network for Small Object Tracking

Marvasti-Zadeh, S. M., Khaghani, J., Ghanei-Yakhdan, H., Shohreh Kasaei, B., & Cheng, L. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69532-3_36 · Cited by 31

Dynamic feature fusion with spatial-temporal context for robust object tracking

Nai, K., Li, Z., & Wang, H. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108775 · Cited by 31

Deep Siamese Network With Motion Fitting for Object Tracking in Satellite Videos

Ruan, L., Guo, Y., Yang, D., & Chen, Z. (2022) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2022.3158652 · Cited by 31

A Collaborative Learning Tracking Network for Remote Sensing Videos

Li, X., Jiao, L., Zhu, H., Liu, F., Yang, S., Zhang, X., Wang, S., & Qu, R. (2022) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2022.3182993 · Cited by 32

Thermal UAV Image Super-Resolution Guided by Multiple Visible Cues

Zhao, Z., Zhang, Y., Li, C., Xiao, Y., & Tang, J. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3234058 · Cited by 31

Learning Cross-Attention Discriminators via Alternating Time–Space Transformers for Visual Tracking

Wang, W., Zhang, K., Su, Y., Wang, J., & Wang, Q. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3282905 · Cited by 31

Learning diverse fine-grained features for thermal infrared tracking

Yang, C., Liu, Q., Li, G., Pan, H., & He, Z. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121577 · Cited by 30

A Transformer-Based Network for Hyperspectral Object Tracking

Gao, L., Chen, L., Liu, P., Jiang, Y., Xie, W., & Li, Y. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3325049 · Cited by 30

Multi-Step Temporal Modeling for UAV Tracking

Yuan, X., Xu, T., Liu, X., Wang, Y., Qin, H., Fang, Y., & Li, J. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3375366 · Cited by 32

Beyond SOT: Tracking Multiple Generic Objects at Once

Mayer, C., Danelljan, M., Yang, M., Ferrari, V., Gool, L. V., & Kuznetsova, A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00668 · Cited by 33

Deep compare: A study on using convolutional neural networks to compare image patches

Zagoruyko, S., & Komodakis, N. (2017) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2017.10.007 · Cited by 31

License plate recognition via convolutional neural networks

Wang, Q. (2017) · IEEE International Conference on Software Engineering and Service Science (ICSESS) · doi:10.1109/icsess.2017.8343061 · Cited by 30

Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending

Yang, X., Mirmehdi, M., & Burghardt, T. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00034 · Cited by 30

Deep-SST-Eddies: A Deep Learning Framework to Detect Oceanic Eddies in Sea Surface Temperature Images

Moschos, E., Schwander, O., Stegner, A., & Gallinari, P. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053909 · Cited by 30

OSCD: A one-shot conditional object detection framework

Fu, K., Zhang, T., Zhang, Y., & Sun, X. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.04.092 · Cited by 31

MetricUNet: Synergistic image- and voxel-level learning for precise prostate segmentation via online sampling

He, K., Lian, C., Adeli, E., Huo, J., Gao, Y., Zhang, B., Zhang, J., & Shen, D. G. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102039 · Cited by 30

Self-Supervised Tracking via Target-Aware Data Synthesis

Li, X., Pei, W., Wang, Y., He, Z., Lu, H., & Yang, M. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3231537 · Cited by 31

A background-aware correlation filter with adaptive saliency-aware regularization for visual tracking

Zhang, J., Yuan, T., He, Y., & Wang, J. (2022) · Neural Computing and Applications · doi:10.1007/s00521-021-06771-4 · Cited by 30

Ad 2 Attack: Adaptive Adversarial Attack on Real-Time UAV Tracking

Fu, C., Li, S., Yuan, X., Ye, J., Cao, Z., & Ding, F. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9812056 · Cited by 30

BS-SiamRPN: Hyperspectral Video Tracking based on Band Selection and the Siamese Region Proposal Network

Wang, S., Qian, K., & Chen, P. (2022) · Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing · doi:10.1109/whispers56178.2022.9955025 · Cited by 30

NCSiam: Reliable Matching via Neighborhood Consensus for Siamese-Based Object Tracking

Lai, P., Cheng, G., Zhang, M., Ning, J., Zheng, X., & Han, J. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3329669 · Cited by 31

Face Sketch Synthesis in the Wild via Deep Patch Representation-Based Probabilistic Graphical Model

Peng, C., Wang, N., Li, J., & Gao, X. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2916633 · Cited by 30

Novel event analysis for human-machine collaborative underwater exploration

Cong, Y., Fan, B., Hou, D., Fan, H., Liu, K., & Luo, J. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.106967 · Cited by 30

Learning-based Widget Matching for Migrating GUI Test Cases

Zhang, Y., Zhang, W., Ran, D., Zhu, Q., Dou, C., Hao, D., Xie, T., & Zhang, L. (2024) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3597503.3623322 · Cited by 42

Vehicle Detection and Tracking in UAV Imagery via YOLOv3 and Kalman Filter

Ali, S., Jalal, A., Alatiyyah, M. H., Alnowaiser, K., & Park, J. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.038114 · Cited by 29

Learning modality feature fusion via transformer for RGBT-tracking

Cai, Y., Sui, X., Gu, G., & Chen, Q. (2023) · Infrared Physics & Technology · doi:10.1016/j.infrared.2023.104819 · Cited by 29

Recent Research Progress on Ground-to-Air Vision-Based Anti-UAV Detection and Tracking Methodologies: A Review

Yasmeen, A., & Daescu, O. (2025) · Drones · doi:10.3390/drones9010058 · Cited by 33

Siamese network ensemble for visual tracking

Jiang, C., Xiao, J., Xie, Y., Tillo, T., & Huang, K. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.10.043 · Cited by 29

PASiam: Predicting Attention Inspired Siamese Network, for Space-Borne Satellite Video Tracking

Shao, J., Du, B., Wu, C., & Pingkun, Y. (2019) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2019.00260 · Cited by 29

End-to-end multitask Siamese network with residual hierarchical attention for real-time object tracking

Huang, W., Gu, J. J., Ma, X., & Li, Y. (2020) · Applied Intelligence · doi:10.1007/s10489-019-01605-2 · Cited by 29

Object Detection-Based Video Retargeting With Spatial–Temporal Consistency

Lee, S. J., Lee, S., Cho, S. I., & Kang, S. (2020) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2020.2981652 · Cited by 29

EmgAuth: An EMG-based Smartphone Unlocking System Using Siamese Network

Fan, B., Liu, X., Su, X. J., Hui, P., & Niu, J. (2020) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom45495.2020.9127387 · Cited by 29

Robust Long-Term Object Tracking via Improved Discriminative Model Prediction

Choi, S., Lee, J., Lee, Y., & Hauptmann, A. G. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-68238-5_40 · Cited by 29

Spectrum-aware discriminative deep feature learning for multi-spectral face recognition

Wu, F., Jing, X., Feng, Y., Ji, Y., & Wang, R. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107632 · Cited by 30

Robust visual tracking via spatio-temporal adaptive and channel selective correlation filters

Liang, Y., Liu, Y., Yan, Y., Zhang, L., & Wang, H. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107738 · Cited by 29

Contrastive Transformation for Self-supervised Correspondence Learning

Wang, N., Zhou, W., & Li, H. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i11.17220 · Cited by 29

Robust Online Tracking via Contrastive Spatio-Temporal Aware Network

Yao, S., Zhang, H., Ren, W., Ma, C., Han, X., & Cao, X. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3050314 · Cited by 29

F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking

Zou, H., Cui, J., Kong, X., Zhang, C., Liu, Y., Wen, F., & Li, W. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341120 · Cited by 29

Learning object-uncertainty policy for visual tracking

He, X., & Chen, C. Y. (2021) · Information Sciences · doi:10.1016/j.ins.2021.09.002 · Cited by 29

Multi-Stage Visual Tracking With Siamese Anchor-Free Proposal Network

Han, G., Su, J., Liu, Y., Zhao, Y., & Kwong, S. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3127357 · Cited by 29

SiamDoGe: Domain Generalizable Semantic Segmentation Using Siamese Network

Wu, Z., Wu, X., Zhang, X.-P., Ju, L., & Wang, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19839-7_35 · Cited by 30

On the Importance of Asymmetry for Siamese Representation Learning

Wang, X., Fan, H., Tian, Y., Kihara, D., & Chen, 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/cvpr52688.2022.01607 · Cited by 32

Part-Aware Framework for Robust Object Tracking

Li, S., Zhao, S., Cheng, B. H., & Chen, J. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3232941 · Cited by 30

Hyperspectral video target tracking based on pixel-wise spectral matching reduction and deep spectral cascading texture features

Zhao, D., Zhu, X., Zhang, Z., Arun, P. V., Cao, J., Wang, Q., Zhou, H., Jiang, H., Hu, J., & Qian, K. (2023) · Signal Processing · doi:10.1016/j.sigpro.2023.109033 · Cited by 29

TAT: Targeted backdoor attacks against visual object tracking

Cheng, Z., Wu, B., Zhang, Z., & Zhao, J. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109629 · Cited by 29

Robust visual tracking with extreme point graph-guided annotation: Approach and experiment

Gao, P., Zhang, X., Yang, X., Gao, F., Fujita, H., & Wang, F. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122013 · Cited by 30

Guess where? Actor-supervision for spatiotemporal action localization

Escorcia, V. A., Dao, C. D., Jain, M., Ghanem, B., & Snoek, C. G. M. (2019) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.102886 · Cited by 29

Specific and Collaborative Representations Siamese Network for RGBT Tracking

Liu, Y., Zhou, D., Cao, J., Yan, K., & Geng, L. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3386772 · Cited by 28

A Deep Temporal-Spectral–Spatial Anchor-Free Siamese Tracking Network for Hyperspectral Video Object Tracking

Liu, Z., Zhong, Y., Ma, G., Wang, X., & Zhang, L. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3483072 · Cited by 33

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

Zhang, H., Ni, W., Yan, W., Wu, J., Hui, B., & Xiang, D. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.11.050 · Cited by 28

Robust Visual Tracking via Hierarchical Particle Filter and Ensemble Deep Features

Li, S., Zhao, S., Cheng, B. H., Zhao, E., & Chen, J. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2889457 · Cited by 28

Correlation Filter Selection for Visual Tracking Using Reinforcement Learning

Xie, Y., Xiao, J., Huang, K., Thiyagalingam, J., & Zhao, Y. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2889488 · Cited by 28

Cascaded Correlation Refinement for Robust Deep Tracking

Ge, S., Zhang, C., Li, S., Zeng, D., & Tao, D. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2984256 · Cited by 28

Multi-Hierarchical Independent Correlation Filters For Visual Tracking

Bai, S., He, Z., Dong, Y., & Bai, H. (2020) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme46284.2020.9102759 · Cited by 28

Target Tracking Using a Mean-Shift Occlusion Aware Particle Filter

Bhat, P. G., Subudhi, B. N., Veerakumar, T., Caterina, G. D., & Soraghan, J. J. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3054815 · Cited by 28

How to Train Your Energy-Based Model for Regression

Gustafsson, F., Danelljan, M., Timofte, R., & Schön, T. B. (2020) · British Machine Vision Conference (BMVC) · doi:10.5244/c.34.43 · Cited by 28

Automatic Hyoid Bone Tracking in Real-Time Ultrasound Swallowing Videos Using Deep Learning Based and Correlation Filter Based Trackers

Feng, S., Shea, Q. T. K., Ng, K.-Y., Tang, C.-N., Kwong, E., & Zheng, Y. (2021) · Sensors · doi:10.3390/s21113712 · Cited by 28

Anti-Distractor Active Object Tracking in 3D Environments

Xi, M., Zhou, Y., Chen, Z., Zhou, W., & Li, H. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3107153 · Cited by 29

An Enhanced SiamMask Network for Coastal Ship Tracking

Yang, X., Wang, Y., Wang, N., & Gao, X. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3122330 · Cited by 30

Siamese anchor-free object tracking with multiscale spatial attentions

Zhang, J., Huang, B., Ye, Z., Kuang, L., & Ning, X. (2021) · Scientific Reports · doi:10.1038/s41598-021-02095-4 · Cited by 28

Semi-supervised body parsing and pose estimation for enhancing infant general movement assessment

Ni, H., Xue, Y., Ma, L., Zhang, Q., Li, X., & Huang, X. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102654 · Cited by 31

UTB180: A High-Quality Benchmark for Underwater Tracking

Alawode, B., Guo, Y., Ummar, M., Werghi, N., Dias, J. M. M., Mian, A. S., & Javed, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26348-4_26 · Cited by 29

Shadow-Enhanced Self-Attention and Anchor-Adaptive Network for Video SAR Moving Target Tracking

Bao, J., Zhang, X., Zhang, T., Zeng, T., Yang, Z., Zhan, X., Shi, J., & Wei, S. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3260254 · Cited by 28

Learning Rain Location Prior for Nighttime Deraining

Zhang, F., You, S., Li, Y., & Fu, Y. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01209 · Cited by 28

Learning Traffic Behaviors by Extracting Vehicle Trajectories from Online Video Streams

Ren, X., Wang, D., Laskey, M., & Goldberg, K. Y. (2018) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/coase.2018.8560597 · Cited by 28

Hijacking Tracker: A Powerful Adversarial Attack on Visual Tracking

Yan, X., Chen, X., Jiang, Y., Xia, S., Zhao, Y. J., & Zheng, F. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053574 · Cited by 28

Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables

Sheng, T., & Huber, M. (2020) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3397330 · Cited by 28

SAR Ground Moving Target Refocusing by Combining mRe³ Network and TVβ-LSTM

Zhou, Y., Shi, J., Wang, C., Hu, Y. G., Zhou, Z., Yang, X., Zhang, X., & Wei, S. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3033656 · Cited by 28

BACTrack: Building Appearance Collection for Aerial Tracking

Liu, X., Xu, T., Wang, Y., Yu, Z., Yuan, X., Qin, H., & Li, J. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3340372 · Cited by 27

Mamba-FETrack: Frame-Event Tracking via State Space Model

Huang, J., Wang, S., Wang, S., Wu, Z., Wang, X., & Jiang, B. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-8858-3_1 · Cited by 32

Two-stage Unidirectional Fusion Network for RGBT tracking

Liu, Y., Gao, Z., Cao, Y., & Zhou, D. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.112983 · Cited by 27

Deep Location-Specific Tracking

Yang, L., Liu, R., Zhang, D. D., & Zhang, L. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123381 · Cited by 27

Transfer learning-based discriminative correlation filter for visual tracking

Huang, B., Xu, T., Li, J., Shen, Z., & Chen, Y. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107157 · Cited by 27

Pyramidal Edge-Maps and Attention Based Guided Thermal Super-Resolution

Gupta, H., & Mitra, K. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-67070-2_42 · Cited by 27

SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training

Dai, P., Yang, J., Ye, X., Cheng, X., Luo, J., Song, L., Chen, Y., & Zhao, W. S. (2020) · ACM/IEEE Design Automation Conference (DAC) · doi:10.1109/dac18072.2020.9218710 · Cited by 28

Pairwise learning for medical image segmentation

Wang, R., Cao, S., Ma, K., Zheng, Y., & Meng, D. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101876 · Cited by 27

Vision-Based Target Detection and Tracking System for a Quadcopter

Wu, S., Li, R., Shi, Y., & Liu, Q. (2021) · IEEE Access · doi:10.1109/access.2021.3074413 · Cited by 27

TCDesc: Learning Topology Consistent Descriptors for Image Matching

Pan, H., Chen, Y., He, Z., Meng, F., & Fan, N. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3099846 · Cited by 27

Robust Object Tracking Algorithm for Autonomous Vehicles in Complex Scenes

Cao, J., Song, C., Song, S., Xiao, F., Zhang, X., Liu, Z., & Ang, M. H. (2021) · Remote Sensing · doi:10.3390/rs13163234 · Cited by 27

Robust Data Association Using Fusion of Data-Driven and Engineered Features for Real-Time Pedestrian Tracking in Thermal Images

Muresan, M. P., Nedevschi, S., & Danescu, R. G. (2021) · Sensors · doi:10.3390/s21238005 · Cited by 27

Object Tracking in Satellite Videos Based on Correlation Filter with Multi-Feature Fusion and Motion Trajectory Compensation

Liu, Y., Liao, Y., Lin, C., Jia, Y., Li, Z., & Yang, X. (2022) · Remote Sensing · doi:10.3390/rs14030777 · Cited by 27

Global Instance Tracking: Locating Target More Like Humans

Hu, S., Zhao, X., Huang, L., & Huang, K. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3153312 · Cited by 31

Rank-Based Filter Pruning for Real-Time UAV Tracking

Wang, X., Zeng, D., Zhao, Q., & Li, S. (2022) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme52920.2022.9859656 · Cited by 28

Correlation Filters Based on Multi-Expert and Game Theory for Visual Object Tracking

Ma, S., Zhao, Z., Hou, Z., Zhang, L., Yang, X., & Pu, L. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3178482 · Cited by 27

Online multi-object tracking with δ-GLMB filter based on occlusion and identity switch handling

Abbaspour, M., & Masnadi‐Shirazi, M. A. (2022) · Image and Vision Computing · doi:10.1016/j.imavis.2022.104553 · Cited by 28

Contextualized Spatio-Temporal Contrastive Learning with Self-Supervision

Yuan, L., Qian, R., Cui, Y., Gong, B., Schroff, F., Yang, M., Adam, H., & Liu, T. (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/cvpr52688.2022.01359 · Cited by 28

Memory Network With Pixel-Level Spatio-Temporal Learning for Visual Object Tracking

Zhou, Z., Zhou, X., Chen, Z., Guo, P., Liu, Q., & Zhang, W. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3272319 · Cited by 27

Target-Aware Tracking With Spatial-Temporal Context Attention

He, K., Zhang, C., Xie, S., Li, Z., Wang, Z., & Qin, R.-G. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3370981 · Cited by 28

Adversarial Deep Tracking

Zhao, F., Wang, J., Wu, Y., & Tang, M. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2856540 · Cited by 27

ReMotENet: Efficient Relevant Motion Event Detection for Large-Scale Home Surveillance Videos

Yu, R., Wang, H., & Davis, L. S. (2018) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2018.00183 · Cited by 27

GenDet: Meta Learning to Generate Detectors From Few Shots

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