7 papers
ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering
Zhentao Guo, Chen Duan, Tongkun Guan +3
Despite remarkable progress in multimodal understanding, current MLLMs still exhibit limitations in video text understanding, particularly when semantics emerge through the integra…
InstructTable: Improving Table Structure Recognition Through Instructions
Boming Chen, Zining Wang, Zhentao Guo +5
Table structure recognition (TSR) holds widespread practical importance by parsing tabular images into structured representations, yet encounters significant challenges when proces…
PositionOCR: Augmenting Positional Awareness in Multi-Modal Models via Hybrid Specialist Integration
Chen Duan, Zhentao Guo, Pei Fu +3
In recent years, Multi-modal Large Language Models (MLLMs) have achieved strong performance in OCR-centric Visual Question Answering (VQA) tasks, illustrating their capability to p…
Marten: Visual Question Answering with Mask Generation for Multi-modal Document Understanding
Zining Wang, Tongkun Guan, Pei Fu +7
Multi-modal Large Language Models (MLLMs) have introduced a novel dimension to document understanding, i.e., they endow large language models with visual comprehension capabilities…
A Token-level Text Image Foundation Model for Document Understanding
Tongkun Guan, Zining Wang, Pei Fu +9
In recent years, general visual foundation models (VFMs) have witnessed increasing adoption, particularly as image encoders for popular multi-modal large language models (MLLMs). H…
Multimodal Large Language Models for Text-rich Image Understanding: A Comprehensive Review
Pei Fu, Tongkun Guan, Zining Wang +8
The recent emergence of Multi-modal Large Language Models (MLLMs) has introduced a new dimension to the Text-rich Image Understanding (TIU) field, with models demonstrating impress…