Search Results for author: Songxuan Lai

Found 10 papers, 4 papers with code

PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition

no code implementations29 Jul 2022 Dezhi Peng, Lianwen Jin, Yuliang Liu, Canjie Luo, Songxuan Lai

Utilizing the proposed weakly supervised learning framework, PageNet requires only transcripts to be annotated for real data; however, it can still output detection and recognition results at both the character and line levels, avoiding the labor and cost of labeling bounding boxes of characters and text lines.

Handwritten Chinese Text Recognition Line Detection

SPTS: Single-Point Text Spotting

1 code implementation15 Dec 2021 Dezhi Peng, Xinyu Wang, Yuliang Liu, Jiaxin Zhang, Mingxin Huang, Songxuan Lai, Shenggao Zhu, Jing Li, Dahua Lin, Chunhua Shen, Xiang Bai, Lianwen Jin

For the first time, we demonstrate that training scene text spotting models can be achieved with an extremely low-cost annotation of a single-point for each instance.

Language Modelling Text Spotting

SVC-onGoing: Signature Verification Competition

1 code implementation13 Aug 2021 Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia, Julian Fierrez, Aythami Morales, Javier Ortega-Garcia, Juan Carlos Ruiz-Garcia, Sergio Romero-Tapiador, Santiago Rengifo, Miguel Caruana, Jiajia Jiang, Songxuan Lai, Lianwen Jin, Yecheng Zhu, Javier Galbally, Moises Diaz, Miguel Angel Ferrer, Marta Gomez-Barrero, Ilya Hodashinsky, Konstantin Sarin, Artem Slezkin, Marina Bardamova, Mikhail Svetlakov, Mohammad Saleem, Cintia Lia Szucs, Bence Kovari, Falk Pulsmeyer, Mohamad Wehbi, Dario Zanca, Sumaiya Ahmad, Sarthak Mishra, Suraiya Jabin

This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB and SVC2021_EvalDB, and standard experimental protocols.

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

no code implementations13 Nov 2019 Songxuan Lai, Lianwen Jin, Luojun Lin, Yecheng Zhu, Huiyun Mao

To tackle this issue, this paper proposes to learn dynamic signature representations through ranking synthesized signatures.

Representation Learning

Offline Writer Identification based on the Path Signature Feature

no code implementations3 May 2019 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 contained in a path.

EnsNet: Ensconce Text in the Wild

3 code implementations3 Dec 2018 Shuaitao Zhang, Yuliang Liu, Lianwen Jin, Yaoxiong Huang, Songxuan Lai

The feature of the former is first enhanced by a novel lateral connection structure and then refined by four carefully designed losses: multiscale regression loss and content loss, which capture the global discrepancy of different level features; texture loss and total variation loss, which primarily target filling the text region and preserving the reality of the background.

Image Text Removal

Online Signature Verification using Recurrent Neural Network and Length-normalized Path Signature

no code implementations19 May 2017 Songxuan Lai, Lianwen Jin, Weixin Yang

Inspired by the great success of recurrent neural networks (RNNs) in sequential modeling, we introduce a novel RNN system to improve the performance of online signature verification.

Toward high-performance online HCCR: a CNN approach with DropDistortion, path signature and spatial stochastic max-pooling

no code implementations24 Feb 2017 Songxuan Lai, Lianwen Jin, Weixin Yang

This paper presents an investigation of several techniques that increase the accuracy of online handwritten Chinese character recognition (HCCR).

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