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Found 13 papers, 6 papers with code
StrucTexT: Structured Text Understanding with Multi-Modal Transformers
Due to the complexity of content and layout in VRDs, structured text understanding has been a challenging task.
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network
With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency.
Ranked #1 on
Scene Text Detection
on ICDAR 2015
(Accuracy metric)
Learning Global Structure Consistency for Robust Object Tracking
Unlike many existing trackers that focus on modeling only the target, in this work, we consider the \emph{transient variations of the whole scene}.
Towards Accurate Scene Text Recognition with Semantic Reasoning Networks
Scene text image contains two levels of contents: visual texture and semantic information.
Ranked #4 on
Scene Text Recognition
on ICDAR2013
An End-to-end Video Text Detector with Online Tracking
Most existing methods attempt to enhance the performance of video text detection by cooperating with video text tracking, but treat these two tasks separately.
A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
Detecting scene text of arbitrary shapes has been a challenging task over the past years.
Ranked #29 on
Scene Text Detection
on ICDAR 2015
Editing Text in the Wild
Specifically, we propose an end-to-end trainable style retention network (SRNet) that consists of three modules: text conversion module, background inpainting module and fusion module.
Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes
Previous scene text detection methods have progressed substantially over the past years.
Detecting Text in the Wild with Deep Character Embedding Network
However, text in the wild is usually perspectively distorted or curved, which can not be easily tackled by existing approaches.
TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network
Reading text from images remains challenging due to multi-orientation, perspective distortion and especially the curved nature of irregular text.
WordSup: Exploiting Word Annotations for Character based Text Detection
When applied in scene text detection, we are thus able to train a robust character detector by exploiting word annotations in the rich large-scale real scene text datasets, e. g. ICDAR15 and COCO-text.
Ranked #4 on
Scene Text Detection
on ICDAR 2013
Multi-Oriented Text Detection with Fully Convolutional Networks
In this paper, we propose a novel approach for text detec- tion in natural images.
Ranked #40 on
Scene Text Detection
on ICDAR 2015
Automatic Script Identification in the Wild
With the rapid increase of transnational communication and cooperation, people frequently encounter multilingual scenarios in various situations.
