KCC 2021
Current Result Document :
| 한글제목(Korean Title) |
대규모 영상에서 발현된 표현인식을 위한 멀티모달 딥 그래프 |
| 영문제목(English Title) |
Multimodal Deep Graph Fusion for Evoked Expression Recognition in Large-Scale Videos |
| 저자(Author) |
트엄안광
호녁흰
양형정
김수형
이귀상
오아란
Anh-Quang Duong
Ngoc-Huynh Ho
Hyung-Jeong Yang
Soo-Hyung Kim
Gueesang Lee
A Ran Oh
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| 원문수록처(Citation) |
VOL 48 NO. 01 PP. 0709 ~ 0711 (2021. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Emotion recognition in the wild faces with large variances in input signals, multiple sources of noise that will challenge the machine to learn approximate ground truth. In this paper, we propose a jointbased fusion model, called deep graph fusion, to leverage the combination of visual-audio representations for evoked prediction of viewers' expression from videos. We evaluate the proposed method using the Evoked Expression from Videos (EEV) dataset and our experimental results demonstrate that our proposed algorithm outperforms baseline models. |
| 키워드(Keyword) |
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| 파일첨부 |
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