1 code implementation • 16 Mar 2023 • Shukang Yin, Shiwei Wu, Tong Xu, Shifeng Liu, Sirui Zhao, Enhong Chen
Automatic Micro-Expression (ME) spotting in long videos is a crucial step in ME analysis but also a challenging task due to the short duration and low intensity of MEs.
no code implementations • 3 Jan 2023 • Sirui Zhao, Huaying Tang, Xinglong Mao, Shifeng Liu, Hanqing Tao, Hao Wang, Tong Xu, Enhong Chen
To solve the problem of ME data hunger, we construct a dynamic spontaneous ME dataset with the largest current ME data scale, called DFME (Dynamic Facial Micro-expressions), which includes 7, 526 well-labeled ME videos induced by 671 participants and annotated by more than 20 annotators throughout three years.
1 code implementation • Findings (EMNLP) 2021 • Shifeng Liu, Yifang Sun, Bing Li, Wei Wang, Florence T. Bourgeois, Adam G. Dunn
The rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials.
no code implementations • 3 Dec 2019 • Shifeng Liu, Yifang Sun, Bing Li, Wei Wang, Xiang Zhao
To tackle Named Entity Recognition (NER) tasks, supervised methods need to obtain sufficient cleanly annotated data, which is labor and time consuming.
no code implementations • 1 Mar 2016 • Shifeng Liu, Zheng Hu, Sujit Dey, Xin Ke
Based on a real world telecom dataset including CDRs and preference of more than $550K$ users for several months, we verified that correlation does exist between online preference in such \textit{ambiguous} social network.