Category: Publication

VAD Emotion Control in Visual Art Captioning via Disentangled Multimodal Representation

by affclab

Ryo Ueda, Hiromi Narimatsu, Yusuke Miyao and Shiro Kumano, in Proc. International Conference on Affective Computing and Intelligent Interaction (ACII

Publication

State-Aware Deep Item Response Theory Using Student Facial Features

by affclab

Yan Zhou, Kenji Suzuki and Shiro Kumano, Frontiers in Artificial Intelligence, 2024 Jan 4;6:1324279, 2024. This paper introduces a novel

Publication

Emotion-Controllable Impression Utterance Generation for Visual Art

by affclab

Ryo Ueda, Hiromi Narimatsu, Yusuke Miyao and Shiro Kumano, in Proc. International Conference on Affective Computing and Intelligent Interaction (ACII

Publication

Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty

by affclab

This paper has been presented at AISTATS 2023, one of the top theory-oriented AI conferences. Abstract Two important aspects of

Publication

Consistent Smile Intensity Estimation from Wearable Optical Sensors

by affclab

Katsutoshi Masai, Monica Perusquıa-Hernandez, Maki Sugimoto, Shiro Kumano and Toshitaka Kimura International Conference on Affective Computing & Intelligent Interaction (ACII

Publication

Cross-Linguistic Study on Affective Impression and Language for Visual Art Using Neural Speaker

by affclab

Hiromi Narimatsu, Ryo Ueda and Shiro Kumano International Conference on Affective Computing & Intelligent Interaction (ACII 2022) Visual art is

Publication

Deep Explanatory Polytomous Item-Response Model for Predicting Idiosyncratic Affective Ratings

by affclab

Yan Zhou, Tsukasa Ishigaki and Shiro Kumano International Conference on Affective Computing & Intelligent Interaction (ACII 2021) Towards explainable affective