4 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 3 cited
StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding
Jinshan Zeng, Yefei Wang, Qi Chen +3
The generation of Chinese fonts has a wide range of applications. The currently predominated methods are mainly based on deep generative models, especially the generative adversari…
cs.SE2022★ 4 cited
CodeGen-Test: An Automatic Code Generation Model Integrating Program Test Information
Maosheng Zhong, Gen Liu, Hongwei Li +3
Automatic code generation is to generate the program code according to the given natural language description. The current mainstream approach uses neural networks to encode natura…