5 papers
UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters
Yongkun Du, Zhineng Chen, Yazhen Xie +6
Text and formulas constitute the core informational components of many documents. Accurately and efficiently recognizing both is crucial for developing robust and generalizable doc…
LRANet++: Low-Rank Approximation Network for Accurate and Efficient Text Spotting
Yuchen Su, Zhineng Chen, Yongkun Du +3
End-to-end text spotting aims to jointly optimize text detection and recognition within a unified framework. Despite significant progress, designing an accurate and efficient end-t…
MDiff4STR: Mask Diffusion Model for Scene Text Recognition
Yongkun Du, Miaomiao Zhao, Songlin Fan +3
Mask Diffusion Models (MDMs) have recently emerged as a promising alternative to auto-regressive models (ARMs) for vision-language tasks, owing to their flexible balance of efficie…
SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition
Yongkun Du, Zhineng Chen, Hongtao Xie +2
Connectionist temporal classification (CTC)-based scene text recognition (STR) methods, e.g., SVTR, are widely employed in OCR applications, mainly due to their simple architecture…
Out of Length Text Recognition with Sub-String Matching
Yongkun Du, Zhineng Chen, Caiyan Jia +2
Scene Text Recognition (STR) methods have demonstrated robust performance in word-level text recognition. However, in real applications the text image is sometimes long due to dete…