Výsledky vyhledávání - "Jeong, Jae‐Yeop"

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Human Reaction Intensity Estimation with Ensemble of Multi-task Networks

Autor: Oh, JiYeon, Kim, Daun, Jeong, Jae-Yeop, Hong, Yeong-Gi, Jeong, Jin-Woo

Facial expression in-the-wild is essential for various interactive computing domains. Especially, "Emotional Reaction Intensity" (ERI) is an important topic in the facial expression recognition task. In this paper, we propose a multi-emotional task l

Externí odkaz: http://arxiv.org/abs/2303.09240

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Learning from Synthetic Data: Facial Expression Classification based on Ensemble of Multi-task Networks

Autor: Jeong, Jae-Yeop, Hong, Yeong-Gi, Oh, JiYeon, Hong, Sumin, Jeong, Jin-Woo, Jung, Yuchul

Facial expression in-the-wild is essential for various interactive computing domains. Especially, "Learning from Synthetic Data" (LSD) is an important topic in the facial expression recognition task. In this paper, we propose a multi-task learning-ba

Externí odkaz: http://arxiv.org/abs/2207.10025

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Akademický článek

High-performance RuO2/CNT paper electrode as cathode for anion exchange membrane water electrolysis

Autor: Jeong, Jae-Yeop, Lee, Jong Min, Park, Yoo Sei, Jin, Song, Myeong, Shin-Woo, Heo, Sungjun, Lee, Hoseok, Albers, Justin Georg, Choi, Young-Woo, Seo, Min Ho, Choi, Sung Mook, Lee, Jooyoung

Publikováno v: In Applied Catalysis B: Environment and Energy 5 November 2024 356

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Facial Expression Recognition based on Multi-head Cross Attention Network

Autor: Jeong, Jae-Yeop, Hong, Yeong-Gi, Kim, Daun, Jung, Yuchul, Jeong, Jin-Woo

Facial expression in-the-wild is essential for various interactive computing domains. In this paper, we proposed an extended version of DAN model to address the VA estimation and facial expression challenges introduced in ABAW 2022. Our method produc

Externí odkaz: http://arxiv.org/abs/2203.13235

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