16 citations · 43 across the 11 of their papers we have counts for
6 papers · 1 filter
Hierarchical Text Spotter for Joint Text Spotting and Layout Analysis
Shangbang Long, Siyang Qin, Yasuhisa Fujii +2
We propose Hierarchical Text Spotter (HTS), a novel method for the joint task of word-level text spotting and geometric layout analysis. HTS can recognize text in an image and iden…
ICDAR 2023 Competition on Hierarchical Text Detection and Recognition
Shangbang Long, Siyang Qin, Dmitry Panteleev +3
We organize a competition on hierarchical text detection and recognition. The competition is aimed to promote research into deep learning models and systems that can jointly perfor…
Text Reading Order in Uncontrolled Conditions by Sparse Graph Segmentation
Renshen Wang, Yasuhisa Fujii, Alessandro Bissacco
Text reading order is a crucial aspect in the output of an OCR engine, with a large impact on downstream tasks. Its difficulty lies in the large variation of domain specific layout…
Unified Line and Paragraph Detection by Graph Convolutional Networks
Shuang Liu, Renshen Wang, Michalis Raptis +1
We formulate the task of detecting lines and paragraphs in a document into a unified two-level clustering problem. Given a set of text detection boxes that roughly correspond to wo…
Towards End-to-End Unified Scene Text Detection and Layout Analysis
Shangbang Long, Siyang Qin, Dmitry Panteleev +3
Scene text detection and document layout analysis have long been treated as two separate tasks in different image domains. In this paper, we bring them together and introduce the t…
Post-OCR Paragraph Recognition by Graph Convolutional Networks
Renshen Wang, Yasuhisa Fujii, Ashok C. Popat
We propose a new approach for paragraph recognition in document images by spatial graph convolutional networks (GCN) applied on OCR text boxes. Two steps, namely line splitting and…