18 citations · 39 across the 16 of their papers we have counts for
8 papers · 1 filter
Predicting the Original Appearance of Damaged Historical Documents
Zhenhua Yang, Dezhi Peng, Yongxin Shi +3
Historical documents encompass a wealth of cultural treasures but suffer from severe damages including character missing, paper damage, and ink erosion over time. However, existing…
Revisiting Tampered Scene Text Detection in the Era of Generative AI
Chenfan Qu, Yiwu Zhong, Fengjun Guo +1
The rapid advancements of generative AI have fueled the potential of generative text image editing, meanwhile escalating the threat of misinformation spreading. However, existing f…
TongGu: Mastering Classical Chinese Understanding with Knowledge-Grounded Large Language Models
Jiahuan Cao, Dezhi Peng, Peirong Zhang +4
Classical Chinese is a gateway to the rich heritage and wisdom of ancient China, yet its complexities pose formidable comprehension barriers for most modern people without speciali…
CBench: A Comprehensive Classical Chinese Understanding Benchmark for Large Language Models
Jiahuan Cao, Yongxin Shi, Dezhi Peng +2
Classical Chinese Understanding (CCU) holds significant value in preserving and exploration of the outstanding traditional Chinese culture. Recently, researchers have attempted to…
DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks
Jiaxin Zhang, Dezhi Peng, Chongyu Liu +2
Document image restoration is a crucial aspect of Document AI systems, as the quality of document images significantly influences the overall performance. Prevailing methods addres…
HierCode: A Lightweight Hierarchical Codebook for Zero-shot Chinese Text Recognition
Yuyi Zhang, Yuanzhi Zhu, Dezhi Peng +5
Text recognition, especially for complex scripts like Chinese, faces unique challenges due to its intricate character structures and vast vocabulary. Traditional one-hot encoding m…
SwinTextSpotter v2: Towards Better Synergy for Scene Text Spotting
Mingxin Huang, Dezhi Peng, Hongliang Li +6
End-to-end scene text spotting, which aims to read the text in natural images, has garnered significant attention in recent years. However, recent state-of-the-art methods usually…
PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction
Zening Lin, Jiapeng Wang, Teng Li +4
Document pair extraction aims to identify key and value entities as well as their relationships from visually-rich documents. Most existing methods divide it into two separate task…