21 citations · 34 across the 3 of their papers we have counts for
5 papers
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition
Yue Jin, Tianqing Zheng, Chao Gao +1
Analyzing human affect is vital for human-computer interaction systems. Most methods are developed in restricted scenarios which are not practical for in-the-wild settings. The Aff…
Curriculum-Meta Learning for Order-Robust Continual Relation Extraction
Tongtong Wu, Xuekai Li, Yuan-Fang Li +4
Continual relation extraction is an important task that focuses on extracting new facts incrementally from unstructured text. Given the sequential arrival order of the relations, t…
Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition
Wenxuan Wang, Yanwei Fu, Qiang Sun +7
Affective computing and cognitive theory are widely used in modern human-computer interaction scenarios. Human faces, as the most prominent and easily accessible features, have att…
A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition
Wenxuan Wang, Qiang Sun, Tao Chen +5
The recent research of facial expression recognition has made a lot of progress due to the development of deep learning technologies, but some typical challenging problems such as…
Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge
Ziqi Zheng, Chenjie Cao, Xingwei Chen +1
The continuous dimensional emotion modelled by arousal and valence can depict complex changes of emotions. In this paper, we present our works on arousal and valence predictions fo…