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20152023
most citedDetecting Curve Text in the Wild: New Dataset and New Solution

212 citations · 1k across the 74 of their papers we have counts for

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Showing 2019Show all

13 papers · 1 filter

cs.CV2019★ 8 cited

Decoupled Attention Network for Text Recognition

Tianwei Wang, Yuanzhi Zhu, Lianwen Jin +5

Text recognition has attracted considerable research interests because of its various applications. The cutting-edge text recognition methods are based on attention mechanisms. How…

cs.CV2019★ 3 cited

Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection

Yuliang Liu, Tong He, Hao Chen +5

Multi-orientation scene text detection has recently gained significant research attention. Previous methods directly predict words or text lines, typically by using quadrilateral s…

cs.CV2019★ 1 cited

SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-world Verification

Songxuan Lai, Lianwen Jin, Luojun Lin +2

An open research problem in automatic signature verification is the skilled forgery attacks. However, the skilled forgeries are very difficult to acquire for representation learnin…

cs.CV2019★ 2 cited

Air-Writing Translater: A Novel Unsupervised Domain Adaptation Method for Inertia-Trajectory Translation of In-air Handwriting

Songbin Xu, Yang Xue, Xin Zhang +1

As a new way of human-computer interaction, inertial sensor based in-air handwriting can provide a natural and unconstrained interaction to express more complex and richer informat…

cs.CV2019★ 12 cited

ICDAR 2019 Competition on Large-scale Street View Text with Partial Labeling -- RRC-LSVT

Yipeng Sun, Zihan Ni, Chee-Kheng Chng +9

Robust text reading from street view images provides valuable information for various applications. Performance improvement of existing methods in such a challenging scenario heavi…

cs.CV2019★ 30 cited

ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)

Chee-Kheng Chng, Yuliang Liu, Yipeng Sun +11

This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) that consists of three major challenges: i) scene text detection, ii) scene text recogn…

cs.CV2019★ 1 cited

Adaptive Embedding Gate for Attention-Based Scene Text Recognition

Xiaoxue Chen, Tianwei Wang, Yuanzhi Zhu +2

Scene text recognition has attracted particular research interest because it is a very challenging problem and has various applications. The most cutting-edge methods are attention…

cs.CV2019★ 13 cited

Omnidirectional Scene Text Detection with Sequential-free Box Discretization

Yuliang Liu, Sheng Zhang, Lianwen Jin +3

Scene text in the wild is commonly presented with high variant characteristics. Using quadrilateral bounding box to localize the text instance is nearly indispensable for detection…

cs.CV2019★ 3 cited

Offline Writer Identification based on the Path Signature Feature

Songxuan Lai, Lianwen Jin

In this paper, we propose a novel set of features for offline writer identification based on the path signature approach, which provides a principled way to express information con…

cs.CV2019

Aggregation Cross-Entropy for Sequence Recognition

Zecheng Xie, Yaoxiong Huang, Yuanzhi Zhu +3

In this paper, we propose a novel method, aggregation cross-entropy (ACE), for sequence recognition from a brand new perspective. The ACE loss function exhibits competitive perform…

cs.CV2019

Tightness-aware Evaluation Protocol for Scene Text Detection

Yuliang Liu, Lianwen Jin, Zecheng Xie +3

Evaluation protocols play key role in the developmental progress of text detection methods. There are strict requirements to ensure that the evaluation methods are fair, objective…

cs.AI2019★ 18 cited

Logic Rules Powered Knowledge Graph Embedding

Pengwei Wang, Dejing Dou, Fangzhao Wu +2

Large scale knowledge graph embedding has attracted much attention from both academia and industry in the field of Artificial Intelligence. However, most existing methods concentra…

cs.CV2019★ 12 cited

A Multi-Object Rectified Attention Network for Scene Text Recognition

Canjie Luo, Lianwen Jin, Zenghui Sun

Irregular text is widely used. However, it is considerably difficult to recognize because of its various shapes and distorted patterns. In this paper, we thus propose a multi-objec…