OCTrack: Benchmarking the Open-Corpus Multi-Object Tracking Article Swipe
Zekun Qian
,
Ruize Han
,
Wei Feng
,
Junhui Hou
,
Linqi Song
,
Song Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2407.14047
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2407.14047
We study a novel yet practical problem of open-corpus multi-object tracking (OCMOT), which extends the MOT into localizing, associating, and recognizing generic-category objects of both seen (base) and unseen (novel) classes, but without the category text list as prompt. To study this problem, the top priority is to build a benchmark. In this work, we build OCTrackB, a large-scale and comprehensive benchmark, to provide a standard evaluation platform for the OCMOT problem. Compared to previous datasets, OCTrackB has more abundant and balanced base/novel classes and the corresponding samples for evaluation with less bias. We also propose a new multi-granularity recognition metric to better evaluate the generative object recognition in OCMOT. By conducting the extensive benchmark evaluation, we report and analyze the results of various state-of-the-art methods, which demonstrate the rationale of OCMOT, as well as the usefulness and advantages of OCTrackB.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2407.14047
- https://arxiv.org/pdf/2407.14047
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402855588
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402855588Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2407.14047Digital Object Identifier
- Title
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OCTrack: Benchmarking the Open-Corpus Multi-Object TrackingWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-07-19Full publication date if available
- Authors
-
Zekun Qian, Ruize Han, Wei Feng, Junhui Hou, Linqi Song, Song WangList of authors in order
- Landing page
-
https://arxiv.org/abs/2407.14047Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2407.14047Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2407.14047Direct OA link when available
- Concepts
-
Benchmarking, Object (grammar), Computer science, Tracking (education), Artificial intelligence, Computer vision, Natural language processing, Business, Sociology, Marketing, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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