13 citations · 33 across the 16 of their papers we have counts for
17 papers
HRVDA: High-Resolution Visual Document Assistant
Chaohu Liu, Kun Yin, Haoyu Cao +6
Leveraging vast training data, multimodal large language models (MLLMs) have demonstrated formidable general visual comprehension capabilities and achieved remarkable performance a…
Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models
Xin Li, Yunfei Wu, Xinghua Jiang +6
Recently, the advent of Large Visual-Language Models (LVLMs) has received increasing attention across various domains, particularly in the field of visual document understanding (V…
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
Chaoyou Fu, Renrui Zhang, Zihan Wang +15
The surge of interest towards Multi-modal Large Language Models (MLLMs), e.g., GPT-4V(ision) from OpenAI, has marked a significant trend in both academia and industry. They endow L…
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
Haoyu Cao, Changcun Bao, Chaohu Liu +6
We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including…
Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution
Jianfeng Kuang, Wei Hua, Dingkang Liang +4
Visual information extraction (VIE), which aims to simultaneously perform OCR and information extraction in a unified framework, has drawn increasing attention due to its essential…
Looking and Listening: Audio Guided Text Recognition
Wenwen Yu, Mingyu Liu, Biao Yang +5
Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective…
Turning a CLIP Model into a Scene Text Detector
Wenwen Yu, Yuliang Liu, Wei Hua +3
The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown great potential in various downstream tasks via leveraging the pretrained vision and language k…
Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation
Hao Liu, Xin Li, Mingming Gong +5
Recently, Table Structure Recognition (TSR) task, aiming at identifying table structure into machine readable formats, has received increasing interest in the community. While impr…
TaCo: Textual Attribute Recognition via Contrastive Learning
Chang Nie, Yiqing Hu, Yanqiu Qu +3
As textual attributes like font are core design elements of document format and page style, automatic attributes recognition favor comprehensive practical applications. Existing ap…
GMN: Generative Multi-modal Network for Practical Document Information Extraction
Haoyu Cao, Jiefeng Ma, Antai Guo +5
Document Information Extraction (DIE) has attracted increasing attention due to its various advanced applications in the real world. Although recent literature has already achieved…
OS-MSL: One Stage Multimodal Sequential Link Framework for Scene Segmentation and Classification
Ye Liu, Lingfeng Qiao, Di Yin +4
Scene segmentation and classification (SSC) serve as a critical step towards the field of video structuring analysis. Intuitively, jointly learning of these two tasks can promote e…
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation
Jiquan Li, Junliang Guo, Yongxin Zhu +4
The task of Grammatical Error Correction (GEC) has received remarkable attention with wide applications in Natural Language Processing (NLP) in recent years. While one of the key p…
Relational Representation Learning in Visually-Rich Documents
Xin Li, Yan Zheng, Yiqing Hu +5
Relational understanding is critical for a number of visually-rich documents (VRDs) understanding tasks. Through multi-modal pre-training, recent studies provide comprehensive cont…
The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training
Hao Liu, Xinghua Jiang, Xin Li +3
The self-supervised Masked Image Modeling (MIM) schema, following "mask-and-reconstruct" pipeline of recovering contents from masked image, has recently captured the increasing int…
Neural Collaborative Graph Machines for Table Structure Recognition
Hao Liu, Xin Li, Bing Liu +3
Recently, table structure recognition has achieved impressive progress with the help of deep graph models. Most of them exploit single visual cues of tabular elements or simply com…
NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition
Hao Liu, Xinghua Jiang, Xin Li +3
Recently, Vision Transformers (ViT), with the self-attention (SA) as the de facto ingredients, have demonstrated great potential in the computer vision community. For the sake of t…
PuzzleNet: Scene Text Detection by Segment Context Graph Learning
Hao Liu, Antai Guo, Deqiang Jiang +2
Recently, a series of decomposition-based scene text detection methods has achieved impressive progress by decomposing challenging text regions into pieces and linking them in a bo…