activity
20172022
most citedTowards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

28 citations · 37 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Pushing the Performance Limit of Scene Text Recognizer without Human Annotation

Caiyuan Zheng, Hui Li, Seon-Min Rhee +3

Scene text recognition (STR) attracts much attention over the years because of its wide application. Most methods train STR model in a fully supervised manner which requires large…

cs.CV2020★ 2 cited

Where to Look and How to Describe: Fashion Image Retrieval with an Attentional Heterogeneous Bilinear Network

Haibo Su, Peng Wang, Lingqiao Liu +3

Fashion products typically feature in compositions of a variety of styles at different clothing parts. In order to distinguish images of different fashion products, we need to extr…

cs.CV2020

A Robust Attentional Framework for License Plate Recognition in the Wild

Linjiang Zhang, Peng Wang, Hui Li +3

Recognizing car license plates in natural scene images is an important yet still challenging task in realistic applications. Many existing approaches perform well for license plate…

cs.CV2019★ 7 cited

Towards End-to-End Text Spotting in Natural Scenes

Peng Wang, Hui Li, Chunhua Shen

Text spotting in natural scene images is of great importance for many image understanding tasks. It includes two sub-tasks: text detection and recognition. In this work, we propose…

cs.CV2017★ 28 cited

Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

Hui Li, Peng Wang, Chunhua Shen

In this work, we jointly address the problem of text detection and recognition in natural scene images based on convolutional recurrent neural networks. We propose a unified networ…