A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition
文献类型：会议论文
| 作者 | Peng, Min3 ; Wang, Chongyang2; Bi, Tao2; Shi, Yu3; Zhou, Xiangdong3; Chen, Tong1
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| 出版日期 | 2019 |
| 会议日期 | September 3, 2019 - September 6, 2019 |
| 会议地点 | Cambridge, United kingdom |
| DOI | 10.1109/ACII.2019.8925525 |
| 英文摘要 | The automatic recognition of micro-expression has been boosted ever since the successful introduction of deep learning approaches. As researchers working on such topics are moving to learn from the nature of micro-expression, the practice of using deep learning techniques has evolved from processing the entire video clip of micro-expression to the recognition on apex frame. Using the apex frame is able to get rid of redundant video frames, but the relevant temporal evidence of micro-expression would be thereby left out. This paper proposes a novel Apex-Time Network (ATNet)to recognize micro-expression based on spatial information from the apex frame as well as on temporal information from the respective-adjacent frames. Through extensive experiments on three benchmarks, we demonstrate the improvement achieved by learning such temporal information. Specially, the model with such temporal information is more robust in cross-dataset validations. © 2019 IEEE. |
| 会议录 | 8th International Conference on Affective Computing and Intelligent Interaction, ACII 2019
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| 语种 | 英语 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/9782]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 作者单位 | 1.College of Electronic and Information Engineering, Southwest University, Chongqing, China 2.UCL Interaction Centre, University College London, London, United Kingdom; 3.Intelligent Security Center, Chongqing Institute of Green and Intelligent Technology, Chongqing, China; |
| 推荐引用方式 GB/T 7714 | Peng, Min,Wang, Chongyang,Bi, Tao,et al. A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition[C]. 见:. Cambridge, United kingdom. September 3, 2019 - September 6, 2019. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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