Publications
📜 Preprints
Hyeonyu Kim*, Jongeun Kim*, Jeonghun Kang, Sanguk Park, Dongchan Park and Taehwan Kim, CVPR 2022 LOng-form VidEo Understanding (LOVEU) challenge track3 [tech report].Â
Hyosun Park, Yongsik Jo, Seokun Kang, Taehwan Kim, M. James Jee, Deeper, Sharper, Faster: Application of Efficient Transformer to Galaxy Image Restoration [arXiv]
📜 Peer-reviewed Publication List
Jinsik Bang and Taehwan Kim, Environmental Understanding Generation with M-LLM for Embodied AI, Â IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Embodied AI Workshop, 2024Â
Taegyeong Lee*, Soyeong Kwon* and Taehwan Kim, Grid Diffusion Models for Text-to-Video Generation, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024 [pdf][project page]
Jaeyeon Bae*, Seokhoon Jeong*, Seokun Kang, Namgi Han, Jae-Yon Lee, Hyounghun Kim and Taehwan Kim, Sound of Story: Multi-modal Storytelling with Audio, Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 [pdf][project page]Â
Jongeun Kim, Minchung Kim and Taehwan Kim, Effective Slogan Generation with Noise Perturbation, ACM International Conference on Information and Knowledge Management (CIKM), 2023 (short paper) [pdf][project page]Â
Taegyeong Lee, Jeonghun Kang, Hyeonyu Kim and Taehwan Kim, Generating Realistic Images from In-the-wild Sounds, IEEE/CVF International Conference on Computer Vision (ICCV), 2023 [pdf][project page]
Seok-Un Kang, Minsu Shin and Taehwan Kim, Galaxy Morphological Classification with Deformable Attention Transformer, NeurIPS 2022 Machine Learning and the Physical Sciences workshop, 2022Â
Hyeshin Chu, Joohee Kim, Seongouk Kim, Hongkyu Lim, Hyunwook Lee, Seungmin Jin, Jongeun Lee, Taehwan Kim and Sungahn Ko, An Empirical Study on How People Perceive AI-generated Music, ACM Conference on Information and Knowledge Management (CIKM), 2022Â
Seyed Hamidreza Mohammadi and Taehwan Kim, One-shot voice conversion with disentangled representations by leveraging phonetic posteriorgrams, Interspeech, 2019 [pdf]
Chao Yang, Taehwan Kim, Ruizhe Wang, Hao Peng and C.-C. Jay Kuo, Show, attend and translate: Unsupervised image translation with self-regularization and attention, IEEE Transactions on Image Processing 28 (10), 4845-4856 (2019) [pdf]
Chao Yang, Taehwan Kim, Ruizhe Wang, Hao Peng and C.-C. Jay Kuo, ESTHER: Extremely Simple Image Translation Through Self-Regularization, British Machine Vision Conference (BMVC), 2018 [pdf]
Seyed Hamidreza Mohammadi and Taehwan Kim, Investigation of Using Disentangled and Interpretable Representations for One-shot Cross-lingual Voice Conversion, Interspeech, 2018 [pdf]
Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari and Karen Livescu, Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation, Computer Speech and Language, 2017 [pdf]
Sarah Taylor, Taehwan Kim, Yisong Yue, James Krahe, Anastasio Garcia Rodriguez, Jessica Hodgins, Moshe Mahler, Iain Matthews, A Deep Learning Approach for Generalized Speech Animation, ACM Conference on Computer Graphics (SIGGRAPH), 2017 [pdf][supplementary][demo video]
Taehwan Kim, Weiran Wang, Hao Tang and Karen Livescu, Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 (Best Student Paper of Speech and Language Processing) [pdf]
Taehwan Kim, Yisong Yue, Sarah Taylor and Iain Matthews, A Decision Tree Framework for Spatiotemporal Sequence Prediction, ACM Conference on Knowledge Discovery and Data Mining (KDD), 2015 [pdf]
Taehwan Kim, Greg Shakhnarovich and Karen Livescu, Fingerspelling Recognition with semi-Markov Conditional Random Fields, IEEE International Conference on Computer Vision (ICCV), 2013 [pdf]
Taehwan Kim, Karen Livescu and Greg Shakhnarovich, American Sign Language Fingerspelling Recognition With Phonological Feature-based Tandem Models, IEEE Workshop on Spoken Language Technology (SLT), 2012 [pdf]
Taehwan Kim, Greg Shakhnarovich and Raquel Urtasun, Sparse Coding for Learning Interpretable Spatio-temporal Primitives, Neural Information Processing Systems (NIPS), 2010 [pdf]
Jihie Kim, Erin Shaw, Saul Wyner, Taehwan Kim and Jia Li, Discerning Affect in Student Discussions, Annual Meeting of the Cognitive Science Society (CogSci), 2010
Jihie Kim, Jia Li and Taehwan Kim: Identifying student online discussions with unanswered questions, K-CAP, 2009
Jihie Kim, Taehwan Kim and Jia Li, Identifying unresolved issues in online students discussions: A multi-phase dialogue classification approach, Proc. of the AI in Education Conference (AIED), 2009