Search Results for author:
Found 11 papers, 8 papers with code
Hierarchical Text Spotter for Joint Text Spotting and Layout Analysis
We propose Hierarchical Text Spotter (HTS), a novel method for the joint task of word-level text spotting and geometric layout analysis.
ICDAR 2023 Competition on Hierarchical Text Detection and Recognition
We organize a competition on hierarchical text detection and recognition.
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction
In FormNetV2, we introduce a centralized multimodal graph contrastive learning strategy to unify self-supervised pre-training for all modalities in one loss.
Towards End-to-End Unified Scene Text Detection and Layout Analysis
In this paper, we bring them together and introduce the task of unified scene text detection and layout analysis.
UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World
Synthetic data has been a critical tool for training scene text detection and recognition models.
A New Perspective for Flexible Feature Gathering in Scene Text Recognition Via Character Anchor Pooling
Irregular scene text recognition has attracted much attention from the research community, mainly due to the complexity of shapes of text in natural scene.
Rethinking Irregular Scene Text Recognition
Reading text from natural images is challenging due to the great variety in text font, color, size, complex background and etc..
SynthText3D: Synthesizing Scene Text Images from 3D Virtual Worlds
Different from the previous methods which paste the rendered text on static 2D images, our method can render the 3D virtual scene and text instances as an entirety.
Scene Text Detection and Recognition: The Deep Learning Era
As an important research area in computer vision, scene text detection and recognition has been inescapably influenced by this wave of revolution, consequentially entering the era of deep learning.
Automatic Judgment Prediction via Legal Reading Comprehension
It has been studied for several decades mainly by lawyers and judges, considered as a novel and prospective application of artificial intelligence techniques in the legal field.
TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes
Driven by deep neural networks and large scale datasets, scene text detection methods have progressed substantially over the past years, continuously refreshing the performance records on various standard benchmarks.
Ranked #2 on
Curved Text Detection
on SCUT-CTW1500
