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Paper Abstract and Keywords
Presentation 2022-02-21 14:25
A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation
Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) The prediction of visual sentiment can be useful to understand users' behaviors. Emotion theories underlying the sentiment labels are different for each dataset. Thus, previous visual sentiment prediction cannot predict the sentiment labels that are different types from those of training data. To handle sentiment labels defined by different emotion theories, this paper proposes a visual sentiment prediction method based on few-shot learning using knowledge distillation. Concretely, we train a convolutional neural network for few-shot learning as a teacher model using an auxiliary loss in self-supervised learning. Furthermore, we train a student model using knowledge distillation, which improves the generalization ability of the model. Moreover, we use the student model to predict the sentiment labels of new data that have different sentiment labels from the training data. We have confirmed the effectiveness of the proposed method through experiments using open datasets.
Keyword (in Japanese) (See Japanese page) 
(in English) knowledge distillation / visual sentiment prediction / few-shot learning / emotion theory / / / /  
Reference Info. ITE Tech. Rep., vol. 46, no. 6, ME2022-49, pp. 171-175, Feb. 2022.
Paper # ME2022-49 
Date of Issue 2022-02-14 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Conference Date 2022-02-21 - 2022-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2022-02-AIT-ME-MMS-IE-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation 
Sub Title (in English)  
Keyword(1) knowledge distillation  
Keyword(2) visual sentiment prediction  
Keyword(3) few-shot learning  
Keyword(4) emotion theory  
1st Author's Name Yingrui Ye  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Yuya Moroto  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Keisuke Maeda  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Takahiro Ogawa  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
5th Author's Name Miki Haseyama  
5th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Date Time 2022-02-21 14:25:00 
Presentation Time 15 
Registration for ME 
Paper # ITE-MMS2022-24,ITE-ME2022-49,ITE-AIT2022-24 
Volume (vol) ITE-46 
Number (no) no.6 
Page pp.171-175 
#Pages ITE-5 
Date of Issue ITE-MMS-2022-02-14,ITE-ME-2022-02-14,ITE-AIT-2022-02-14 

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