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SOTVerse: A User-Defined Task Space of Single Object Tracking
Shiyu, Hu1,2; Xin, Zhao1,2; Kaiqi Huang1,2,3
Source PublicationInternational Journal of Computer Vision
ISSN0920-5691
2023-10
Volume132Issue:3Pages:1-59
Corresponding AuthorZhao, Xin(xzhao@nlpr.ia.ac.cn) ; Huang, Kaiqi(kqhuang@nlpr.ia.ac.cn)
Abstract

Single object tracking (SOT) research falls into a cycle—trackers perform well on most benchmarks but quickly fail in challenging scenarios, causing researchers to doubt the insufficient data content and take more effort to construct larger datasets with more challenging situations. However, inefficient data utilization and limited evaluation methods more seriously hinder SOT research. The former causes existing datasets can not be exploited comprehensively, while the latter neglects challenging factors in the evaluation process. In this article, we systematize the representative benchmarks and form a single object tracking metaverse (SOTVerse)—a user-defined SOT task space to break through the bottleneck. We first propose a 3E Paradigm to describe tasks by three components (i.e., environment, evaluation, and executor). Then, we summarize task characteristics, clarify the organization standards, and construct SOTVerse with 12.56 million frames. Specifically, SOTVerse automatically labels challenging factors per frame, allowing users to generate user-defined spaces efficiently via construction rules. Besides, SOTVerse provides two mechanisms with new indicators and successfully evaluates trackers under various subtasks. Consequently, SOTVerse first provides a strategy to improve resource utilization in the computer vision area, making research more standardized. The SOTVerse, toolkit, evaluation server, and results are available at http://metaverse.aitestunion.com.

KeywordSingle object tracking Experimental environment Evaluation system Performance analysis
DOI10.1007/s11263-023-01908-5
WOS KeywordPERFORMANCE ; TIME
Indexed BySCI
Language英语
Funding ProjectYouth Innovation Promotion Association of the Chinese Academy of Sciences
Funding OrganizationYouth Innovation Promotion Association of the Chinese Academy of Sciences
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:001176990700015
PublisherSPRINGER
Sub direction classification目标检测、跟踪与识别
planning direction of the national heavy laboratory智能能力评估
Paper associated data
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/54542
Collection复杂系统认知与决策实验室_智能系统与工程
Corresponding AuthorXin, Zhao; Kaiqi Huang
Affiliation1.School of Artificial Intelligence, University of Chinese Academy of Sciences,
2.Institute of Automation, Chinese Academy of Sciences
3.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Shiyu, Hu,Xin, Zhao,Kaiqi Huang. SOTVerse: A User-Defined Task Space of Single Object Tracking[J]. International Journal of Computer Vision,2023,132(3):1-59.
APA Shiyu, Hu,Xin, Zhao,&Kaiqi Huang.(2023).SOTVerse: A User-Defined Task Space of Single Object Tracking.International Journal of Computer Vision,132(3),1-59.
MLA Shiyu, Hu,et al."SOTVerse: A User-Defined Task Space of Single Object Tracking".International Journal of Computer Vision 132.3(2023):1-59.
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