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.
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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
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
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