activity
20172020
most citedChinese Typography Transfer

19 citations · 32 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20201 cited

Prime-Aware Adaptive Distillation

Youcai Zhang, Zhonghao Lan, Yuchen Dai +4

Knowledge distillation(KD) aims to improve the performance of a student network by mimicing the knowledge from a powerful teacher network. Existing methods focus on studying what k…

cs.CV2020

Data Uncertainty Learning in Face Recognition

Jie Chang, Zhonghao Lan, Changmao Cheng +1

Modeling data uncertainty is important for noisy images, but seldom explored for face recognition. The pioneer work, PFE, considers uncertainty by modeling each face image embeddin…

cs.CV20195 cited

Handwritten Chinese Font Generation with Collaborative Stroke Refinement

Chuan Wen, Jie Chang, Ya Zhang +4

Automatic character generation is an appealing solution for new typeface design, especially for Chinese typefaces including over 3700 most commonly-used characters. This task has t…

cs.CV2018

An Element Sensitive Saliency Model with Position Prior Learning for Web Pages

Yujun Gu, Jie Chang, Ya Zhang +1

Understanding human visual attention is important for multimedia applications. Many studies have attempted to learn from eye-tracking data and build computational saliency predicti…

cs.CV20177 cited

Chinese Typeface Transformation with Hierarchical Adversarial Network

Jie Chang, Yujun Gu, Ya Zhang

In this paper, we explore automated typeface generation through image style transfer which has shown great promise in natural image generation. Existing style transfer methods for…

cs.CV201719 cited

Chinese Typography Transfer

Jie Chang, Yujun Gu

In this paper, we propose a new network architecture for Chinese typography transformation based on deep learning. The architecture consists of two sub-networks: (1)a fully convolu…