The DOI matches its Crossref record; 56 of the 59 references it cites were found in a registry or an index.
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Open accessAbstract
Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployments in resource-constrained applications. In this work, we present LightTrack, which uses neural architecture search (NAS) to design more lightweight and efficient object trackers. Comprehensive experiments show that our LightTrack is effective. It can find trackers that achieve superior performance compared to handcrafted SOTA trackers, such as SiamRPN++ [30] and Ocean [56], while using much fewer model Flops and parameters. Moreover, when deployed on resource-constrained mobile chipsets, the discovered trackers run much faster. For example, on Snapdragon 845 Adreno GPU, LightTrack runs 12× faster than Ocean, while using 13× fewer parameters and 38× fewer Flops. Such improvements might narrow the gap between academic models and industrial deployments in object tracking task. LightTrack is released at here.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
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
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
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
Squeeze-and-Excitation Networks
Hu, J., Shen, L., & Sun, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00745 · Cited by 35,667
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L.-C. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00474 · Cited by 28,755
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
Xception: Deep Learning with Depthwise Separable Convolutions
Chollet, F. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.195 · Cited by 20,380
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Tan, M., & Le, Q. V. (2019) · arXiv · doi:10.48550/arxiv.1905.11946 · Cited by 17,072
Howard, A., Sandler, M., Chen, B., Wang, W., Chen, L.-C., Tan, M., Chu, G., Vasudevan, V., Zhu, Y., Pang, R., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00140 · Cited by 9,708
Research works printed but not linked: 2
- liu, 2019, DARTS: differentiable architecture searc, ICLRE
- 10.1109/CVPR42600.2020.00661 · DOI · Paper page
Cited by
Sorted by citations
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
“SiamFC [2] RT-MDNet [23] ECO [10] Ocean [69] LightTrack [60] SiamRPN++ [28] ATOM [11] DiMP50 [3] TransT [6] STARK-S50 STARK-ST50 STARK-ST101”
Self-citationVisible-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
Self-citationGeneralized Relation Modeling for Transformer Tracking
Gao, S., Zhou, C., & Zhang, J. (2023) · 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/cvpr52729.2023.01792 · Cited by 271
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook
Javed, S., Danelljan, M., Khan, F. S., Khan, M. H., Felsberg, M., & Matas, J. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3212594 · Cited by 201
Efficient Visual Tracking with Exemplar Transformers
Blatter, P., Kanakis, M., Danelljan, M., & Gool, L. V. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00162 · Cited by 183
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
Sun, H., Yang, W., Feng, H., Zheng, Y., Mei, Q., Ren, D., & Yu, M. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106314 · Cited by 136
Exploring Lightweight Hierarchical Vision Transformers for Efficient Visual Tracking
Kang, B., Chen, X., Wang, D., Peng, H., & Lu, H. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00881 · Cited by 148
Self-citationSingle-Model and Any-Modality for Video Object Tracking
Wu, Z., Zheng, J., Ren, X., Vasluianu, F.-A., Ma, C., Paudel, D. P., Gool, L. V., & Timofte, R. (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/cvpr52733.2024.01812 · Cited by 143
Xia, R., Chen, Y., & Ren, B. (2022) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2022.02.004 · Cited by 112
Towards Real-World Visual Tracking With Temporal Contexts
Cao, Z., Huang, Z., Pan, L., Zhang, S., Liu, Z., & Fu, C. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3307174 · Cited by 119
Sun, H., Li, B., Dan, Z., Hu, W., Du, B., Yang, W., & Wan, J. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.03.017 · Cited by 107
SmallTrack: Wavelet Pooling and Graph Enhanced Classification for UAV Small Object Tracking
Xue, Y., Jin, G., Shen, T., Tan, L., Wang, N., Gao, J., & Wang, L. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3305728 · Cited by 110
Bi, Y., Xue, B., Mesejo, P., Cagnoni, S., & Zhang, M. (2022) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2022.3220747 · Cited by 104
Separable Self and Mixed Attention Transformers for Efficient Object Tracking
Gopal, G. Y., & Amer, M. A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00657 · Cited by 100
Efficient Visual Tracking via Hierarchical Cross-Attention Transformer
Chen, X., Kang, B., Wang, D., Li, D., & Lu, H. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25085-9_26 · Cited by 101
Self-citationFEAR: Fast, Efficient, Accurate and Robust Visual Tracker
Borsuk, V., Vei, R., Kupyn, O., Martyniuk, T., Krashenyi, I., & Matas, J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20047-2_37 · Cited by 102
Siamese object tracking for unmanned aerial vehicle: a review and comprehensive analysis
Fu, C., Lu, K., Zheng, G., Ye, J., Cao, Z., Li, B., & Lu, G. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10558-5 · Cited by 99
Unsupervised Learning of Accurate Siamese Tracking
Shen, Q., Qiao, L., Guo, J., Li, P., Li, X., Li, B., Feng, W., Gan, W., Wu, W., & Ouyang, W. (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/cvpr52688.2022.00793 · Cited by 80
SENSE: Hyperspectral video object tracker via fusing material and motion cues
Chen, Y., Yuan, Q., Tang, Y., Xiao, Y., He, J., & Liu, Z. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102395 · Cited by 81
Adaptive and Background-Aware Vision Transformer for Real-Time UAV Tracking
Li, S., Yang, Y., Zeng, D., & Wang, X. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01286 · Cited by 83
Chen, Y., Yuan, Q., Tang, Y., Xiao, Y., He, J., & Zhang, L. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3347950 · Cited by 74
AVLTrack: Dynamic Sparse Learning for Aerial Vision-Language Tracking
Xue, Y., Zhong, B., Jin, G., Shen, T., Tan, L., Li, N., & Zheng, Y. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3549953 · Cited by 68
Chen, Y., Tang, Y., Xiao, Y., Yuan, Q., Zhang, Y., Liu, F., He, J., & Zhang, L. (2024) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2024.03.013 · Cited by 73
A Survey on Vision-Based Anti Unmanned Aerial Vehicles Methods
Wang, B., Li, Q., Mao, Q., Wang, J., Chen, C. L. P., Shangguan, A., & Zhang, H. (2024) · Drones · doi:10.3390/drones8090518 · Cited by 69
Similarity-Guided Layer-Adaptive Vision Transformer for UAV Tracking
Xue, C., Zhong, B., Liang, Q., Zheng, Y., Li, N., Xue, Y., & Song, S. (2025) · 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/cvpr52734.2025.00631 · Cited by 78
A survey of model compression strategies for object detection
Lyu, Z., Yu, T., Pan, F., Zhang, Y., Luo, J., Zhang, D., Chen, Y., Zhang, B., & Li, G. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17192-x · Cited by 65
Chen, Y., Yuan, Q., Tang, Y., Xiao, Y., He, J., Han, T., Liu, Z., & Zhang, L. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102658 · Cited by 64
WebUAV-3M: A Benchmark for Unveiling the Power of Million-Scale Deep UAV Tracking
Zhang, C., Huang, G., Liu, L., Huang, S., Yang, Y., Wan, X., Ge, S., & Tao, D. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3232854 · Cited by 62
Handling Occlusion in UAV Visual Tracking With Query-Guided Redetection
Xue, Y., Shen, T., Jin, G., Tan, L., Wang, N., Wang, L., & Gao, J. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3440378 · Cited by 56
Adaptive Siamese Tracking with a Compact Latent Network
Dong, X., Shen, J., Porikli, F., Luo, J., & Shao, L. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3230064 · Cited by 50
Cross-Modality Distillation for Multi-Modal Tracking
Zhang, T., Zhang, Q., Debattista, K., & Han, J. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3555485 · Cited by 46
Bi-level Alignment for Cross-Domain Crowd Counting
Gong, S., Zhang, S., Yang, J. J., Dai, D., & Schiele, B. (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/cvpr52688.2022.00739 · Cited by 45
Visual Object Tracking in First Person Vision
Dunnhofer, M., Furnari, A., Farinella, G. M., & Micheloni, C. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01694-6 · Cited by 52
AutoEnhancer: Transformer on U-Net Architecture Search for Underwater Image Enhancement
Tang, Y., Iwaguchi, T., Kawasaki, H., Sagawa, R., & Furukawa, R. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26313-2_8 · Cited by 40
Efficient Evaluation Methods for Neural Architecture Search: A Survey
Song, X., Xie, X., Lv, Z., Yen, G. G., Ding, W., Lv, J., & Sun, Y. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3477457 · Cited by 52
Adaptively bypassing vision transformer blocks for efficient visual tracking
Yang, X., Zeng, D., Wang, X., Wu, Y., Ye, H., Zhao, Q., & Li, S. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111278 · Cited by 39
PromptVT: Prompting for Efficient and Accurate Visual Tracking
Zhang, M., Zhang, Q., Song, W., Huang, D., & He, Q. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3376582 · Cited by 41
Online Learning Samples and Adaptive Recovery for Robust RGB-T Tracking
Liu, J., Luo, Z., & Xiong, X. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3288853 · Cited by 34
Wei, Q., Zeng, B., Liu, J., He, L., & Zeng, G. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610022 · Cited by 40
Decode-MOT: How Can We Hurdle Frames to Go Beyond Tracking-by-Detection?
Lee, S.-H., Park, D.-H., & Bae, S. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3298538 · Cited by 33
Hyperspectral Video Tracking With Spectral–Spatial Fusion and Memory Enhancement
Chen, Y., Yuan, Q., Hong, X., Tang, Y., Xiao, Y., He, J., Guan, R., Liu, X., & Zhang, L. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3569479 · Cited by 34
Visual and Language Collaborative Learning for RGBT Object Tracking
Wang, J., Liu, F., Jiao, L., Gao, Y., Wang, H., Li, S., Li, L., Chen, P., & Liu, X. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3436878 · Cited by 30
PHTrack: Prompting for Hyperspectral Video Tracking
Chen, Y., Tang, Y., Su, X. B., Li, J., Xiao, Y., He, J., & Yuan, Q. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3461316 · Cited by 38
Resource-Efficient RGBD Aerial Tracking
Yang, J., Gao, S., Li, Z., Zheng, F., & Leonardis, A. (2023) · 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/cvpr52729.2023.01285 · Cited by 30
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
Correlation-Embedded Transformer Tracking: A Single-Branch Framework
Xie, F., Yang, W., Wang, C., Chu, L., Cao, Y., Ma, C., & Zeng, W. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3448254 · Cited by 35
Chen, Y., Yuan, Q., Tang, Y., Wang, X., Xiao, Y., He, J., Lihe, Z., & Jin, X. (2025) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2025.05.008 · Cited by 27
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
McNally, W., Vats, K., Wong, A. K. C., & McPhee, J. (2021) · IEEE Access · doi:10.1109/access.2021.3118207 · Cited by 48
Li, W., Wang, Z., Mai, R., Ren, P., Zhang, Q., Zhou, Y., Xu, N., Zhuang, J., Xin, B., Gao, L., et al. (2023) · Visual Intelligence · doi:10.1007/s44267-023-00006-x · Cited by 27
EMTrack: Efficient Multimodal Object Tracking
Liu, C., Guan, Z., Lai, S., Liu, Y., Lu, H., & Wang, D. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3494725 · Cited by 23
Self-citationLightweight 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
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
Zhang, Z., Zhu, X., Zhao, D., Arun, P. V., Zhou, H., Qian, K., & Hu, J. (2022) · Remote Sensing · doi:10.3390/rs14235958 · Cited by 21
Fisher Pruning for Real-Time UAV Tracking
Wu, W., Zhong, P., & Li, S. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892373 · Cited by 20
CLASH: Complementary Learning With Neural Architecture Search for Gait Recognition
Dou, H., Zhang, P., Zhao, Y., Jin, L., & Li, X. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3360870 · Cited by 20
Exploring Dynamic Transformer for Efficient Object Tracking
Zhu, J., Chen, X. Y., Diao, H., Li, S., He, J.-Y., Li, C., Luo, B., Wang, D., & Lu, H. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3545752 · Cited by 22
Self-citationSiamSTC: Updatable Siamese tracking network via Spatio-Temporal Context
Wei, B., Chen, H., Ding, Q., & Luo, H. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110286 · Cited by 20
Chen, Y., Tang, Y., Yuan, Q., & Zhang, L. (2024) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2024.103741 · Cited by 19
Video-Based Detection of Freezing of Gait in Daily Clinical Practice in Patients With Parkinsonism
Kondo, Y., Bando, K., Suzuki, I., Miyazaki, Y., Nishida, D., Hara, T., Kadone, H., & Suzuki, K. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3413055 · Cited by 21
A Transformer-based visual object tracker via learning immediate appearance change
Li, Y., Liu, X., Yuan, D., Wang, J., Wu, P., & Liu, J. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110705 · Cited by 18
Siamese Object Tracking for Vision-Based UAM Approaching with Pairwise Scale-Channel Attention
Zheng, G., Fu, C., Ye, J., Li, B., Lu, G., & Pan, J. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9982189 · Cited by 18
A Global-Local Tracking Framework Driven by Both Motion and Appearance for Infrared Anti-UAV
Li, Y., Yuan, D., Sun, M., Wang, H., Liu, X., & Liu, J. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00304 · Cited by 19
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
Hu, W., Wang, Q., Gao, J. G., Li, B., & Maybank, S. J. (2024) · Journal of Computer Science and Technology · doi:10.1007/s11390-023-3788-3 · Cited by 18
Xu, P., Wang, K., Hassan, M. R., Hassan, M. M., & Chen, C. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3177442 · Cited by 17
Guo, S., Long, Z., Wu, Z., Chen, Q., Pitas, I., & Fan, R. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3618378 · Cited by 16
Spatio-temporal matching for siamese visual tracking
Zhang, J., Dai, K., Li, Z., Wei, R., & Wang, Y. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.11.093 · Cited by 17
Bidirectional Interaction of CNN and Transformer Feature for Visual Tracking
Sun, B., Wang, Z., Wang, S., Cheng, Y., & Ning, J. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3376690 · Cited by 19
Divert More Attention to Vision-Language Object Tracking
Guo, M., Zhang, Z., Jing, L., Ling, H., & Fan, H. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3409078 · Cited by 19
A transformer based visual tracker with restricted token interaction and knowledge distillation
Liu, N., & Zhang, Y. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112736 · Cited by 15
Tracking Small and Fast Moving Objects: A Benchmark
Zhang, Z., Wu, F., Qiu, Y., Liang, J., & Li, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26293-7_33 · Cited by 15
Wang, B., Li, W., Zhang, B., Liu, Y., & Du, J. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3325672 · Cited by 14
CTIFTrack: Continuous Temporal Information Fusion for object track
Zhang, Z., Guo, Z., Wang, L., & Li, Y. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125654 · Cited by 15
Transformer-based moving target tracking method for Unmanned Aerial Vehicle
Sun, N., Zhao, J., Wang, G., Liu, C., Liu, P., Tang, X., & Han, J. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105483 · Cited by 14
Scale-Aware Siamese Object Tracking for Vision-Based UAM Approaching
Zheng, G., Fu, C., Ye, J., Li, B., Lu, G., & Pan, J. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3228197 · Cited by 15
An Occlusion-Aware Tracker With Local-Global Features Modeling in UAV Videos
Jin, Q., Han, Y., Wang, W., Tang, L., Li, J., & Deng, C. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3368035 · Cited by 16
Enabling deformation slack in tracking with temporally even correlation filters
Zhang, Y., Pan, H., & Wang, J. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106839 · Cited by 18
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking
Yu, H., Zhu, P., Zhang, K., Wang, Y., Zhao, S., Wang, L., Zhang, T., & Hu, Q. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3208605 · Cited by 15
Li, Y., Liu, J., & Teng, Y. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109714 · Cited by 13
Yu, H., Liu, D., Zhang, Z., & Wang, J. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3312488 · Cited by 12
Online Multi-Scale Classification and Global Feature Modulation for Robust Visual Tracking
Gao, Q., Yin, M., Wu, X., Liu, D., & Bo, Y. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3343949 · Cited by 13
Exploring the complementarity between convolution and transformer matching for visual tracking
Wang, Z., Li, M., Pei, W., Lu, G., & Chen, F. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112184 · Cited by 12
Online learning discriminative sparse convolution networks for robust UAV object tracking
Qi, X., Xu, Z., Wang, H., Chen, Y., & Tao, L. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112742 · Cited by 12
Spatial-Temporal Contextual Aggregation Siamese Network for UAV Tracking
Chen, Q., Wang, X., Liu, F., Zuo, Y., & Liu, C. (2024) · Drones · doi:10.3390/drones8090433 · Cited by 11
STAR: A Unified Spatiotemporal Fusion Framework for Satellite Video Object Tracking
Chen, Y., Yuan, Q., Xiao, Y., Tang, Y., He, J., & Han, T. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3585112 · Cited by 12
Probabilistic Assignment With Decoupled IoU Prediction for Visual Tracking
Zhang, D., Xiao, X., Zheng, Z., Jiang, Y., & Yang, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3367537 · Cited by 11
Joint Response and Background Learning for UAV Visual Tracking
Wang, B., Li, W., Zhang, B., & Liu, Y. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611308 · Cited by 11
Wang, K., Wang, Z., Zhang, X., & Liu, M. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.126202 · Cited by 11
Gao, J. G., Lin, S., Wang, S., Kou, Y., Li, Z., Li, L., Zhang, C., Zhang, X., Wang, Y., & Hu, W. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-024-02327-w · Cited by 12
A lightweight and efficient one-stage detection framework
Huang, J., Chen, J., & Wang, H. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108520 · Cited by 11
Chen, Q., Liu, J., Liu, F., Xu, F., & Liu, C. (2024) · Drones · doi:10.3390/drones8010024 · Cited by 9
SiamHOT: Siamese High-Order Transformer for Aerial Tracking
Chen, Q., Zuo, Y., Wang, B., Liu, J., & Liu, C. (2024) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2024.3381181 · Cited by 9
Visual tracking with pyramidal feature fusion and transformer based model predictor
Gong, X., Zhang, Y., & Hu, S. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108461 · Cited by 9
Exploring the Feature Extraction and Relation Modeling For Light-Weight Transformer Tracking
Zheng, J., Liang, M., Huang, S., & Ning, J. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73397-0_7 · Cited by 9
Deep Learning for Single-object Tracking: A Survey
Zhou, J., Yao, Y., & Yang, R. (2022) · IEEE International Conference on Software Engineering and Artificial Intelligence (SEAI) · doi:10.1109/seai55746.2022.9832135 · Cited by 9
Efficient object tracking algorithm based on lightweight Siamese networks
Feng, Z., & Wang, H. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.107976 · Cited by 9
A real-time siamese tracker deployed on UAVs
Shen, H., Lin, D., & Song, T. (2022) · Journal of Real-Time Image Processing · doi:10.1007/s11554-021-01190-z · Cited by 9
Real‐time visual tracking design for an unmanned aerial vehicle in cluttered environments
Liang, J., Yi, P., Li, W., Zuo, J., Zhu, B., & Wang, Y. (2024) · Optimal Control Applications and Methods · doi:10.1002/oca.3175 · Cited by 8
DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model
Chen, Y., Li, Y., Li, S., Lv, S., & Lin, F. (2025) · Applied Sciences · doi:10.3390/app15073862 · Cited by 8
Metadata
- Authors
- Yan, B., Peng, H., Wu, K., Wang, D., Fu, J., & Lu, H.
- Affiliations
- Dalian University of Technology (CN)
- Microsoft Research Asia (China) (CN)
- Sun Yat-sen University (CN)
- Venue
- 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2021-06
- Pages
- 15175-15184
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W3173344965
- Cited by
- 277
- References
- 59
- Citations by year
- 2026: 32 · 2025: 72 · 2024: 77 · 2023: 50 · 2022: 40 · 2021: 6
- FWCI
- 14.15
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- object tracking, lightweight neural networks, neural architecture search, resource-constrained deployment, mobile devices, model compression
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
