21 citations · 61 across the 10 of their papers we have counts for
12 papers
OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich Image Reasoning
Mingxin Huang, Yongxin Shi, Dezhi Peng +3
Recent advancements in multimodal slow-thinking systems have demonstrated remarkable performance across various visual reasoning tasks. However, their capabilities in text-rich ima…
DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming
Jiaxin Zhang, Wentao Yang, Songxuan Lai +2
Current multimodal large language models (MLLMs) face significant challenges in visual document understanding (VDU) tasks due to the high resolution, dense text, and complex layout…
MDoc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout Analysis
Hiuyi Cheng, Peirong Zhang, Sihang Wu +6
Document layout analysis is a crucial prerequisite for document understanding, including document retrieval and conversion. Most public datasets currently contain only PDF document…
Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling
Yongshuai Huang, Ning Lu, Dapeng Chen +5
Table structure recognition aims to extract the logical and physical structure of unstructured table images into a machine-readable format. The latest end-to-end image-to-text appr…
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…
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…
DeRPN: Taking a further step toward more general object detection
Lele Xie, Yuliang Liu, Lianwen Jin +1
Most current detection methods have adopted anchor boxes as regression references. However, the detection performance is sensitive to the setting of the anchor boxes. A proper sett…
Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
Zecheng Xie, Zenghui Sun, Lianwen Jin +2
Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences…
Fully Convolutional Recurrent Network for Handwritten Chinese Text Recognition
Zecheng Xie, Zenghui Sun, Lianwen Jin +2
This paper proposes an end-to-end framework, namely fully convolutional recurrent network (FCRN) for handwritten Chinese text recognition (HCTR). Unlike traditional methods that re…
Improved Deep Convolutional Neural Network For Online Handwritten Chinese Character Recognition using Domain-Specific Knowledge
Weixin Yang, Lianwen Jin, Zecheng Xie +1
Deep convolutional neural networks (DCNNs) have achieved great success in various computer vision and pattern recognition applications, including those for handwritten Chinese char…
DropSample: A New Training Method to Enhance Deep Convolutional Neural Networks for Large-Scale Unconstrained Handwritten Chinese Character Recognition
Weixin Yang, Lianwen Jin, Dacheng Tao +2
Inspired by the theory of Leitners learning box from the field of psychology, we propose DropSample, a new method for training deep convolutional neural networks (DCNNs), and apply…
High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature Maps
Zhuoyao Zhong, Lianwen Jin, Zecheng Xie
Just like its great success in solving many computer vision problems, the convolutional neural networks (CNN) provided new end-to-end approach to handwritten Chinese character reco…