no code implementations • 23 Apr 2024 • Jieru Lin, Danqing Huang, Tiejun Zhao, Dechen Zhan, Chin-Yew Lin
This complexity makes the comprehension of graphic design challenging, for it needs the capability to both recognize the design elements and understand the design.
no code implementations • 14 Mar 2024 • Haohan Weng, Danqing Huang, Yu Qiao, Zheng Hu, Chin-Yew Lin, Tong Zhang, C. L. Philip Chen
In this paper, we present Desigen, an automatic template creation pipeline which generates background images as well as harmonious layout elements over the background.
1 code implementation • 29 Jan 2024 • Jieru Lin, Danqing Huang, Tiejun Zhao, Dechen Zhan, Chin-Yew Lin
Furthermore, based on our observation that pixel space is more sensitive in capturing spatial patterns of graphic layouts (e. g., overlap, alignment), we propose a learning-based locator to detect erroneous tokens which takes the wireframe image rendered from the generated layout sequence as input.
no code implementations • 5 Sep 2023 • Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui
The distributed data analytic system -- Spark is a common choice for processing massive volumes of heterogeneous data, while it is challenging to tune its parameters to achieve high performance.
no code implementations • 1 Jan 2021 • Yuxi Xie, Danqing Huang, Jinpeng Wang, Chin-Yew Lin
Layout representation, which models visual elements in a canvas and their inter-relations, plays a crucial role in graphic design intelligence.
no code implementations • WS 2019 • Qingyu Zhou, Danqing Huang
A math word problem is a narrative with a specific topic that provides clues to the correct equation with numerical quantities and variables therein.
no code implementations • COLING 2018 • Danqing Huang, Jing Liu, Chin-Yew Lin, Jian Yin
Experimental results show that (1) The copy and alignment mechanism is effective to address the two issues; (2) Reinforcement learning leads to better performance than maximum likelihood on this task; (3) Our neural model is complementary to the feature-based model and their combination significantly outperforms the state-of-the-art results.
no code implementations • ACL 2018 • Danqing Huang, Jin-Ge Yao, Chin-Yew Lin, Qingyu Zhou, Jian Yin
To solve math word problems, previous statistical approaches attempt at learning a direct mapping from a problem description to its corresponding equation system.
no code implementations • EMNLP 2017 • Danqing Huang, Shuming Shi, Chin-Yew Lin, Jian Yin
This method learns the mappings between math concept phrases in math word problems and their math expressions from training data.