Scene Text recognition with Full Normalization
Scene text recognition has made significant progress in recent years and has become an important part of the work-flow. The widespread use of mobile devices opens up wide possibilities for using OCR technologies in everyday life. However, lack of training data for new research in this area remains relevant. In this article, we present a new dataset consisting of real shots on smartphones and demonstrate the effectiveness of profile normalization in this task. In addition, the influence of various augmentations during the training of models for analyzing document images on smartphones is studied in detail. Our dataset is publicly available.
Code (0)
등록된 구현이 없습니다.
Tasks
Optical Character Recognition (OCR)Scene Text RecognitionSimilar Papers 제목 키워드 기반
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
Image-based sequence recognition has been a long-standing research topic in computer vision. In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in…
Optical Character Recognition (OCR)Scene Text RecognitionTowards Full-to-Empty Room Generation with Structure-Aware Feature Encoding and Soft Semantic Region-Adaptive Normalization
The task of transforming a furnished room image into a background-only is extremely challenging since it requires making large changes regarding the scene context while still preserving the overall layout and style. In o…
Depth EstimationImage InpaintingLayout GenerationImproved Bilinear Pooling with CNNs
Bilinear pooling of Convolutional Neural Network (CNN) features [22, 23], and their compact variants [10], have been shown to be effective at fine-grained recognition, scene categorization, texture recognition, and visua…
GPUQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)tmVar 3.0: an improved variant concept recognition and normalization tool
Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the pa…
BenchmarkingNeural Text Normalization with Subword Units
Text normalization (TN) is an important step in conversational systems. It converts written text to its spoken form to facilitate speech recognition, natural language understanding and text-to-speech synthesis. Finite st…
Machine TranslationNatural Language Understandingspeech-recognitionSpeech Recognition+6