16 citations · 17 across the 2 of their papers we have counts for
3 papers
cs.CV2023★ 16 cited
TextDiff: Mask-Guided Residual Diffusion Models for Scene Text Image Super-Resolution
Baolin Liu, Zongyuan Yang, Pengfei Wang +5
The goal of scene text image super-resolution is to reconstruct high-resolution text-line images from unrecognizable low-resolution inputs. The existing methods relying on the opti…
cs.CV2023
DocDiff: Document Enhancement via Residual Diffusion Models
Zongyuan Yang, Baolin Liu, Yongping Xiong +6
Removing degradation from document images not only improves their visual quality and readability, but also enhances the performance of numerous automated document analysis and reco…
cs.CV2023★ 1 cited
GDB: Gated convolutions-based Document Binarization
Zongyuan Yang, Yongping Xiong, Guibin Wu
Document binarization is a key pre-processing step for many document analysis tasks. However, existing methods can not extract stroke edges finely, mainly due to the fair-treatment…