한국정보처리학회:학술대회논문집 (Proceedings of the Korea Information Processing Society Conference)

한국정보처리학회 (Korea Information Processing Society)
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얼굴 감정 인식을 위한 로컬 및 글로벌 어텐션 퓨전 네트워크

Local and Global Attention Fusion Network For Facial Emotion Recognition

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  • 김수형 (전남대학교 인공지능융합학과)
  • Minh-Hai Tran (Dept. of Information Technology, HCMC University of Foreign Language Information Technology) ;
  • Tram-Tran Nguyen Quynh (Dept. of Artificial Intelligence Convergence, Chonnam National University) ;
  • Nhu-Tai Do (Dept. of Artificial Intelligence Convergence, Chonnam National University) ;
  • Soo-Hyung Kim (Dept. of Artificial Intelligence Convergence, Chonnam National University)
  • 발행 : 2023.05.18
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초록

Deep learning methods and attention mechanisms have been incorporated to improve facial emotion recognition, which has recently attracted much attention. The fusion approaches have improved accuracy by combining various types of information. This research proposes a fusion network with self-attention and local attention mechanisms. It uses a multi-layer perceptron network. The network extracts distinguishing characteristics from facial images using pre-trained models on RAF-DB dataset. We outperform the other fusion methods on RAD-DB dataset with impressive results.

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과제정보

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1I1A3A04036408) and also supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2021-0-02068, Artificial Intelligence Innovation Hub).