The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.
LabelMe: Online Image Annotation and Applications
Open accessAbstract
Central to the development of computer vision systems is the collection and use of annotated images spanning our visual world. Annotations may include information about the identity, spatial extent, and viewpoint of the objects present in a depicted scene. Such a database is useful for the training and evaluation of computer vision systems. Motivated by the availability of images on the Internet, we introduced a web-based annotation tool that allows online users to label objects and their spatial extent in images. To date, we have collected over 400 000 annotations that span a variety of different scene and object classes. In this paper, we show the contents of the database, its growth over time, and statistics of its usage. In addition, we explore and survey applications of the database in the areas of computer vision and computer graphics. Particularly, we show how to extract the real-world 3-D coordinates of images in a variety of scenes using only the user-provided object annotations. The output 3-D information is comparable to the quality produced by a laser range scanner. We also characterize the space of the images in the database by analyzing 1) statistics of the co-occurrence of large objects in the images and 2) the spatial layout of the labeled images.
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Self-citationBallard, D. H., & Brown, C. M. (1982) · Cited by 5,303
LabelMe: A Database and Web-Based Tool for Image Annotation
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Self-citationLearning realistic human actions from movies
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Badrinarayanan, V., Kendall, A., & Cipolla, R. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2644615 · Cited by 19,631
Hmdb: a large video database for human motion recognition
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ShapeNet: An Information-Rich 3D Model Repository
Chang, A. X., Funkhouser, T. A., Guibas, L. J., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., et al. (2023) · doi:10.5281/zenodo.10089705 · Cited by 1,623
Intelligent detection of fastener defects in ballastless tracks based on deep learning
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A review of current systems for annotation of cell and tissue images in digital pathology
Korzynska, A., Roszkowiak, L., Zak, J., & Siemion, K. (2021) · Biocybernetics and Biomedical Engineering · doi:10.1016/j.bbe.2021.04.012 · Cited by 26
Metadata
- Authors
- Torralba, A., Russell, B. C., & Yuen, J.
- Venue
- Proceedings of the IEEE
- Published
- 2010-08
- Volume
- 98
- Issue
- 8
- Pages
- 1467-1484
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2064985253
- Cited by
- 431
- References
- 89
- FWCI
- 10.69
- Type
- journal article
- Language
- en
- Open access
- green
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