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Semi-Supervised Scene Text Recognition
IEEE Transactions on Image Processing, 2021Scene text recognition has been widely researched with supervised approaches. Most existing algorithms require a large amount of labeled data and some methods even require character-level or pixel-wise supervision information. However, labeled data is expensive, unlabeled data is relatively easy to collect, especially for many languages with fewer ...
Yunze Gao +3 more
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CLIPTER: Looking at the Bigger Picture in Scene Text Recognition
IEEE International Conference on Computer Vision, 2023Reading text in real-world scenarios often requires understanding the context surrounding it, especially when dealing with poor-quality text. However, current scene text recognizers are unaware of the bigger picture as they operate on cropped text images.
Aviad Aberdam +7 more
semanticscholar +1 more source
Class-Aware Mask-Guided Feature Refinement for Scene Text Recognition
Pattern Recognition, 2023Scene text recognition is a rapidly developing field that faces numerous challenges due to the complexity and diversity of scene text, including complex backgrounds, diverse fonts, flexible arrangements, and accidental occlusions.
Mingkun Yang +4 more
semanticscholar +1 more source
CDistNet: Perceiving Multi-domain Character Distance for Robust Text Recognition
International Journal of Computer Vision, 2021The transformer-based encoder-decoder framework is becoming popular in scene text recognition, largely because it naturally integrates recognition clues from both visual and semantic domains.
Tianlun Zheng +4 more
semanticscholar +1 more source
Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
European Conference on Computer Vision, 2021Linguistic knowledge has brought great benefits to scene text recognition by providing semantics to refine character sequences. However, since linguistic knowledge has been applied individually on the output sequence, previous methods have not fully ...
Byeonghu Na, Yoonsik Kim, Sungrae Park
semanticscholar +1 more source
A Novel Text Recognition Scheme using Classification Assisted Digital Image Processing Strategy
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), 2022In the industry of Digital Image Processing, Text Recognition is an important task due to the significance of many classical records available today is in the format of paper record.
M. Tamilselvi +4 more
semanticscholar +1 more source
2020
The article describes the method of image recognition on the example of recognition of Japanese characters. Recognition is carried out by determining the lengths of the contours. After that, the moments of each circuit are compared. Also, taking into account the peculiarities of Japanese characters, the comparison occurs line by line. This approach can
Olha Pohudina +3 more
openaire +1 more source
The article describes the method of image recognition on the example of recognition of Japanese characters. Recognition is carried out by determining the lengths of the contours. After that, the moments of each circuit are compared. Also, taking into account the peculiarities of Japanese characters, the comparison occurs line by line. This approach can
Olha Pohudina +3 more
openaire +1 more source
Self-supervised Character-to-Character Distillation for Text Recognition
IEEE International Conference on Computer Vision, 2022When handling complicated text images (e.g., irregular structures, low resolution, heavy occlusion, and uneven illumination), existing supervised text recognition methods are data-hungry. Although these methods employ large-scale synthetic text images to
Tongkun Guan +4 more
semanticscholar +1 more source
Object Reading: Text Recognition for Object Recognition
2012We propose to use text recognition to aid in visual object class recognition. To this end we first propose a new algorithm for text detection in natural images. The proposed text detection is based on saliency cues and a context fusion step. The algorithm does not need any parameter tuning and can deal with varying imaging conditions. We evaluate three
Karaoglu, S. +2 more
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SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models
IEEE International Conference on Document Analysis and Recognition, 2021For successful scene text recognition (STR) models, synthetic text image generators have alleviated the lack of annotated text images from the real world.
Moonbin Yim +3 more
semanticscholar +1 more source