8 citations · 14 across the 4 of their papers we have counts for
4 papers
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…
Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd Counting
Yunxin Liu, Qiaosi Yi, Jinshan Zeng
The lightweight crowd counting models, in particular knowledge distillation (KD) based models, have attracted rising attention in recent years due to their superiority on computati…
StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding
Jinshan Zeng, Qi Chen, Yunxin Liu +2
The generation of stylish Chinese fonts is an important problem involved in many applications. Most of existing generation methods are based on the deep generative models, particul…
Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background
Qiaosi Yi, Yunxing Liu, Aiwen Jiang +3
Crowd counting is an important task that shown great application value in public safety-related fields, which has attracted increasing attention in recent years. In the current res…