Search Results for author: Shifeng Liu

Found 5 papers, 2 papers with code

AU-aware graph convolutional network for Macro- and Micro-expression spotting

1 code implementation16 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.

Micro-Expression Spotting

More is Better: A Database for Spontaneous Micro-Expression with High Frame Rates

no code implementations3 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.

Sent2Span: Span Detection for PICO Extraction in the Biomedical Text without Span Annotations

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.

PICO Sentence

HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition

no code implementations3 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.

Boundary Detection named-entity-recognition +2

On Tie Strength Augmented Social Correlation for Inferring Preference of Mobile Telco Users

no code implementations1 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.

Collaborative Filtering Marketing

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