The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Word Spotting and Recognition with Embedded Attributes
Abstract
This paper addresses the problems of word spotting and word recognition on images. In word spotting, the goal is to find all instances of a query word in a dataset of images. In recognition, the goal is to recognize the content of the word image, usually aided by a dictionary or lexicon. We describe an approach in which both word images and text strings are embedded in a common vectorial subspace. This is achieved by a combination of label embedding and attributes learning, and a common subspace regression. In this subspace, images and strings that represent the same word are close together, allowing one to cast recognition and retrieval tasks as a nearest neighbor problem. Contrary to most other existing methods, our representation has a fixed length, is low dimensional, and is very fast to compute and, especially, to compare. We test our approach on four public datasets of both handwritten documents and natural images showing results comparable or better than the state-of-the-art on spotting and recognition tasks.
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Cites
Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
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RELATIONS BETWEEN TWO SETS OF VARIATES
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Visual categorization with bags of keypoints
Csurka, G. (2004) · Cited by 4,379
Canonical Correlation Analysis: An Overview with Application to Learning Methods
Hardoon, D. R., Szedmak, S., & Shawe-Taylor, J. (2004) · Neural Computation · doi:10.1162/0899766042321814 · Cited by 3,202
Product Quantization for Nearest Neighbor Search
Jégou, H., Douze, M., & Schmid, C. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.57 · Cited by 2,956
Improving the Fisher Kernel for Large-Scale Image Classification
Perronnin, F., Sánchez, J., & Mensink, T. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15561-1_11 · Cited by 2,588
Describing objects by their attributes
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Learning to detect unseen object classes by between-class attribute transfer
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Self-citation
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Reading text in the wild with convolutional neural networks
Jaderberg, M., Simonyan, K., Vedaldi, A., & Zisserman, A. (2016) · International Journal of Computer Vision · doi:10.1007/s11263-015-0823-z · Cited by 1,191
Focusing Attention: Towards Accurate Text Recognition in Natural Images
Cheng, Z., Bai, F., Xu, Y., Zheng, G., Pu, S., & Zhou, S. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.543 · Cited by 528
Scene Text Detection and Recognition: The Deep Learning Era
Long, S., He, X., & Yao, C. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-020-01369-0 · Cited by 527
DocVQA: A Dataset for VQA on Document Images
Mathew, M., Karatzas, D., & Jawahar, C. V. (2021) · 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) · doi:10.1109/wacv48630.2021.00225 · Cited by 513
AON: Towards Arbitrarily-Oriented Text Recognition
Cheng, Z., Xu, Y., Bai, F., Niu, Y., Pu, S., & Zhou, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00584 · Cited by 292
Metadata
- Authors
- Almazan, J., Gordo, A., Fornes, A., & Valveny, E.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2014-12-01
- Volume
- 36
- Issue
- 12
- Pages
- 2552-2566
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2053317383
- Cited by
- 517
- References
- 53
- FWCI
- 31.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Almazan, J., Gordo, A., Fornes, A., & Valveny, E. (2014). Word Spotting and Recognition with Embedded Attributes. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2014.2339814
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