9 citations · 9 across the 1 of their papers we have counts for
5 papers · 1 filter
Brush Your Text: Synthesize Any Scene Text on Images via Diffusion Model
Lingjun Zhang, Xinyuan Chen, Yaohui Wang +2
Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating m…
Weakly Supervised Scene Text Generation for Low-resource Languages
Yangchen Xie, Xinyuan Chen, Hongjian Zhan +4
A large number of annotated training images is crucial for training successful scene text recognition models. However, collecting sufficient datasets can be a labor-intensive and c…
VGTS: Visually Guided Text Spotting for Novel Categories in Historical Manuscripts
Wenbo Hu, Hongjian Zhan, Xinchen Ma +3
In the field of historical manuscript research, scholars frequently encounter novel symbols in ancient texts, investing considerable effort in their identification and documentatio…
DG-Font: Deformable Generative Networks for Unsupervised Font Generation
Yangchen Xie, Xinyuan Chen, Li Sun +1
Font generation is a challenging problem especially for some writing systems that consist of a large number of characters and has attracted a lot of attention in recent years. Howe…
Channel Attention and Multi-level Features Fusion for Single Image Super-Resolution
Yue Lu, Yun Zhou, Zhuqing Jiang +2
Convolutional neural networks (CNNs) have demonstrated superior performance in super-resolution (SR). However, most CNN-based SR methods neglect the different importance among feat…