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Directions

 
AI is Interactive Computing

Human-centric AI is emerging as a very important field of AI research. We look into how users interact with AI systems, how people can contribute to datasets and other aspects of machine learning and AI system development, as well as how AI can impact humans and society.

  • 2021

  • A survey on deep learning-based Monte Carlo denoising

    Huo, Yuchi, Sung-Eui Yoon
    COMPUTATIONAL VISUAL MEDIA
    2021

  • An experimental study to understand user experience and perception bias occurred by fact-checking messages

    Park, Sungkyu, Park, Jaimie Yejean, Chin,Hyojin, Kang, Jeong-han, Meeyoung Cha
    2021 World Wide Web Conference, WWW 2021
    2021

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  • Bug Report Summarization using Believability Score and Text Ranking

    Koh, Youngji, Sungwon Kang, Lee, Seonah
    2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
    2021

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  • Combined center dispersion loss function for deep facial expression recognition

    ABHILASHA NANDA, Woobin Im, Key-Sun CHOI, Hyun S. Yang
    PATTERN RECOGNITION LETTERS
    2021

  • Deep Regression Network-Assisted Efficient Streamline Generation Method

    Joong Youn Lee, Jinah Park
    IEEE ACCESS
    2021

  • Finding epic moments in live content through deep learning on collective decisions

    HyeonHo Song, Park, Kunwoo, Meeyoung Cha
    EPJ DATA SCIENCE
    2021

  • Instant Panoramic Texture Mapping with Semantic Object Matching for Large-Scale Urban Scene Reproduction

    Park, J, Jeon, Ik-Beom, Sung-Eui Yoon, Woo, W
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
    2021

  • Joint Learning of 3D Shape Retrieval and Deformation

    Uy, Mikaela Angelina, Kim, Vladimir G., Sung Minhyuk, Aigerman, Noam, Chaudhuri, Siddhartha
    2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    2021

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  • Learning to Detect Incongruence in News Headline and Body Text via a Graph Neural Network

    Yoon, Seunghyun, Park, Kunwoo, Lee, Minwoo, Kim, Taegyun, Meeyoung Cha, Jung, Kyomin
    IEEE ACCESS
    2021

  • ReRankMatch: Semi-Supervised Learning with Semantics-Oriented Similarity Representation

    Tran,Trung Quang, Kang,Mingu, Daeyoung KIM
    2021 International Joint Conference on Neural Networks, IJCNN 2021
    2021

  • SetVAE: learning hierarchical composition for generative modeling of set-structured data

    Yoo, Jaehoon, Kim, Jinwoo, Lee, J, seunghoon.hong
    IEEE/CVF Conference on Computer Vision and Pattern Recognition
    2021

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  • The effectiveness of feature attribution methods and its correlation with automatic evaluation scores

    Nguyen, Giang, Daeyoung KIM, Nguyen, Anh
    Thirty-fifth Conference on Neural Information Processing Systems, NeurIPS 2021
    2021

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  • Weakly-Supervised Contrastive Learning in Path Manifold for Monte Carlo Image Reconstruction

    Cho, In-Young, Huo, Yuchi, Sung-Eui Yoon
    ACM TRANSACTIONS ON GRAPHICS
    2021

  • 자기지도학습으로 추론된 특징을 이용한 CT 영상의 보간 방법

    Lim, Joowon, 박진아
    정보과학회논문지
    2021

  • 2020

  • Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

    Park Daehyung, Hoshi, Yuuna, Mahajan, Harshal P., Kim, Ho Keun, Erickson, Zackory, Rogers, Wendy A., Kemp, Charles C.
    ROBOTICS AND AUTONOMOUS SYSTEMS
    2020

  • Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images

    Ali, Sharib, Bhattarai, Binod, Kim Tae Kyun, Rittscher, Jens
    11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020
    2020

  • Data augmentation method for improving the accuracy of human pose estimation with cropped images

    Soonchan Park, Lee, Sang-baek, Jinah Park
    PATTERN RECOGNITION LETTERS
    2020

  • Deep Physiological Affect Network for the Recognition of Human Emotions

    BYUNG HYUNG KIM, Sungho Jo
    IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
    2020

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  • Enhancing Quality of Corpus Annotation: Construction of the Multi-Layer Corpus Annotation and Simplified Validation of the Corpus Annotation

    Noh, Y, KunTae Kim, Minho Lee, CHEOLHUN HEO, Yongbin Jeong, 정유성, Young Gyun Hahm, Oh, Taehwan, Choi, Hyonsu, Park, Seokwon, KIm, Jin-Dong, Key-Sun CHOI
    34th Pacific Asia Conference on Language, Information and Computation (PACLIC 34)
    2020

  • Evaluating Surprise Adequacy for Question Answering

    Seah Kim, Shin Yoo
    42nd IEEE/ACM International Conference on Software Engineering Workshops, ICSEW 2020
    2020

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