Presentation | 2022-05-19 Variational Autoencoders Conditioned by Contrastive Features as Style-Feature Extractors Suguru Yasutomi, Toshihisa Tanaka, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Extracting style features is crucial for investigating the characteristics of data. This paper proposes a variational autoencoder that extracts style features by adding features of contrastive learning as a condition. We can regard the contrastive features as style-independent by assuming that the data augmentation is a perturbation of style. We add the style-independent contrastive features to the input of the decoder, aiming to make the encoder cover the style features for reconstruction. Experiments on MNIST show qualitatively that the proposed method can extract style features. Additional experiments on DAISO-100 evaluate the performance of extracting style quantitatively. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | contrastive learning / variational autoencoders / style extraction |
Paper # | SIP2022-3,BioX2022-3,IE2022-3,MI2022-3 |
Date of Issue | 2022-05-12 (SIP, BioX, IE, MI) |
Conference Information | |
Committee | SIP / BioX / IE / MI / ITE-IST / ITE-ME |
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Conference Date | 2022/5/19(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Kumamoto University Kurokami Campus |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Yukihiro Bandou(NTT) / Hitoshi Imaoka(NEC) / Kazuya Kodama(NII) / Hidekata Hontani(Nagoya Inst. of Tech.) |
Vice Chair | Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) / Takayuki Nakachi(Ryukyu Univ.) / Masatsugu Ichino(Univ. of Electro-Comm.) / Naoyuki Takada(SECOM) / Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo) / Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.) |
Secretary | Toshihisa Tanaka(Xiaomi) / Takayuki Nakachi(Takushoku Univ.) / Masatsugu Ichino(Tokyo Univ. Agri.&Tech.) / Naoyuki Takada(KDDI Research) / Hiroyuki Bandoh(MitsubishiElectric) / Toshihiko Yamazaki(KDDI Research) / Hideaki Haneishi(Nagoya Inst. of Tech.) / Takayuki Kitasaka(Yamaguchi Univ.) / (Univ. of Hyogo) |
Assistant | Taichi Yoshida(UEC) / Seisuke Kyochi(Univ. of Kitakyushu) / Hiroyuki Suzuki(Gunma Univ) / Akihiro Hayasaka(NEC) / Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) |
Paper Information | |
Registration To | Technical Committee on Signal Processing / Technical Committee on Biometrics / Technical Committee on Image Engineering / Technical Committee on Medical Imaging / Technical Group on Information Sensing Technologies / Technical Group on Media Engineering |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Variational Autoencoders Conditioned by Contrastive Features as Style-Feature Extractors |
Sub Title (in English) | |
Keyword(1) | contrastive learning |
Keyword(2) | variational autoencoders |
Keyword(3) | style extraction |
1st Author's Name | Suguru Yasutomi |
1st Author's Affiliation | Tokyo University of Agriculture and Technology(TUAT) |
2nd Author's Name | Toshihisa Tanaka |
2nd Author's Affiliation | Tokyo University of Agriculture and Technology(TUAT) |
Date | 2022-05-19 |
Paper # | SIP2022-3,BioX2022-3,IE2022-3,MI2022-3 |
Volume (vol) | vol.122 |
Number (no) | SIP-28,BioX-29,IE-30,MI-31 |
Page | pp.pp.13-18(SIP), pp.13-18(BioX), pp.13-18(IE), pp.13-18(MI), |
#Pages | 6 |
Date of Issue | 2022-05-12 (SIP, BioX, IE, MI) |