8 citations · 14 across the 4 of their papers we have counts for
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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.CV2021★ 2 cited
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…
cs.CV2021★ 8 cited
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…