activity
20172025
most citedDetecting Curve Text in the Wild: New Dataset and New Solution

212 citations · 480 across the 34 of their papers we have counts for

collaborators
Showing 2019Show all

6 papers · 1 filter

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★ 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★ 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

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…