The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Visual Turing test for computer vision systems
Open accessAbstract
Significance: In computer vision, as in other fields of artificial intelligence, the methods of evaluation largely define the scientific effort. Most current evaluations measure detection accuracy, emphasizing the classification of regions according to objects from a predefined library. But detection is not the same as understanding. We present here a different evaluation system, in which a query engine prepares a written test (“visual Turing test”) that uses binary questions to probe a system’s ability to identify attributes and relationships in addition to recognizing objects.
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Cites
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A fast learning algorithm for deep belief nets
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I.—COMPUTING MACHINERY AND INTELLIGENCE
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Object Detection with Discriminatively Trained Part-Based Models
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Cited by
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.-J., Shamma, D. A., et al. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-016-0981-7 · Cited by 5,107
VQA: Visual Question Answering
Antol, S., Agrawal, A., Lu, J., Mitchell, M., Batra, D., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.279 · Cited by 4,487
Film: Visual reasoning with a general conditioning layer
Perez, E., Strub, F., De Vries, H., Dumoulin, V., & Courville, A. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11671 · Cited by 2,490
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Johnson, J., Hariharan, B., van der Maaten, L., Fei-Fei, L., Zitnick, C. L., & Girshick, R. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.215 · Cited by 1,781
Salient Object Detection: A Benchmark
Borji, A., Cheng, M.-M., Jiang, H., & Li, J. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2487833 · Cited by 1,364
Metadata
- Authors
- Geman, D., Geman, S., Hallonquist, N., & Younes, L.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2015-03-09
- Volume
- 112
- Issue
- 12
- Pages
- 3618-3623
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1983927101
- Cited by
- 321
- References
- 33
- FWCI
- 35.53
- Type
- journal article
- Language
- en
- Open access
- green
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