TAPVid-3D: A Benchmark for Tracking Any Point in 3D Article Swipe
Skanda Koppula
,
Ignacio Rocco
,
Yi Yang
,
Joe Heyward
,
João Carreira
,
Andrew Zisserman
,
Gabriel Brostow
,
Carl Doersch
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2407.05921
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2407.05921
We introduce a new benchmark, TAPVid-3D, for evaluating the task of long-range Tracking Any Point in 3D (TAP-3D). While point tracking in two dimensions (TAP) has many benchmarks measuring performance on real-world videos, such as TAPVid-DAVIS, three-dimensional point tracking has none. To this end, leveraging existing footage, we build a new benchmark for 3D point tracking featuring 4,000+ real-world videos, composed of three different data sources spanning a variety of object types, motion patterns, and indoor and outdoor environments. To measure performance on the TAP-3D task, we formulate a collection of metrics that extend the Jaccard-based metric used in TAP to handle the complexities of ambiguous depth scales across models, occlusions, and multi-track spatio-temporal smoothness. We manually verify a large sample of trajectories to ensure correct video annotations, and assess the current state of the TAP-3D task by constructing competitive baselines using existing tracking models. We anticipate this benchmark will serve as a guidepost to improve our ability to understand precise 3D motion and surface deformation from monocular video. Code for dataset download, generation, and model evaluation is available at https://tapvid3d.github.io
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2407.05921
- https://arxiv.org/pdf/2407.05921
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400485083
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4400485083Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2407.05921Digital Object Identifier
- Title
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TAPVid-3D: A Benchmark for Tracking Any Point in 3DWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-08Full publication date if available
- Authors
-
Skanda Koppula, Ignacio Rocco, Yi Yang, Joe Heyward, João Carreira, Andrew Zisserman, Gabriel Brostow, Carl DoerschList of authors in order
- Landing page
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https://arxiv.org/abs/2407.05921Publisher landing page
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https://arxiv.org/pdf/2407.05921Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2407.05921Direct OA link when available
- Concepts
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Benchmark (surveying), Tracking (education), Point (geometry), Computer science, Artificial intelligence, Computer vision, Mathematics, Psychology, Geography, Geometry, Cartography, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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| abstract_inverted_index.occlusions, | 110 |
| abstract_inverted_index.performance | 29, 81 |
| abstract_inverted_index.smoothness. | 114 |
| abstract_inverted_index.annotations, | 127 |
| abstract_inverted_index.complexities | 103 |
| abstract_inverted_index.constructing | 138 |
| abstract_inverted_index.trajectories | 122 |
| abstract_inverted_index.Jaccard-based | 95 |
| abstract_inverted_index.TAPVid-DAVIS, | 35 |
| abstract_inverted_index.environments. | 78 |
| abstract_inverted_index.spatio-temporal | 113 |
| abstract_inverted_index.three-dimensional | 36 |
| abstract_inverted_index.https://tapvid3d.github.io | 180 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |