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LaSOT: A High-quality Large-scale Single Object Tracking Benchmark
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“LaSO-Text [23] is an extension of LaSOT, featuring a subset of 15 categories with 150 videos.”
From SAM2LONG: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree (2025) · cites this paper as [23]
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Cites
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Metadata
- Authors
- Fan, H., Bai, H., Lin, L., Yang, F., Chu, P., Deng, G., Yu, S., Harshit, Huang, M., Liu, J., Xu, Y., Liao, C., Yuan, L., & Ling, H.
- Affiliations
- Stony Brook University (US)
- Temple University (US)
- Peng Cheng Laboratory (CN)
- Amazon (United States) (US)
- Corresponding author
- Fan, Heng
- ORCID
- Venue
- International Journal of Computer Vision
- Published
- 2020-09-29
- Volume
- 129
- Issue
- 2
- Pages
- 439-461
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W3090155371
- Cited by
- 360
- References
- 95
- Citations by year
- 2026: 91 · 2025: 116 · 2024: 77 · 2023: 43 · 2022: 24 · 2021: 8 · 2020: 1
- FWCI
- 7.39
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International Journal of Computer Vision (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- single object tracking, tracking benchmark, LaSOT, long-term tracking, target occlusion
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