Eun-Sol Kim (김은솔)
I am an Assistant Professor at the Department of Computer Science, Hanyang University. Before joining Hanyang University, I was a Research Scientist at Kakao Brain. I received my Ph.D. degree at Seoul National University under the supervision of Professor Byoung-Tak Zhang.
My research interests include:
- Machine Learning
- Computer Vision
- Large-scale Representation Learning
- Video Understanding
- Human-like Reasoning
News
Mar 3, 2022 | Two papers are accepted at CVPR 2022. |
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Feb 26, 2022 | One paper is accepted at ACL 2022. |
Sep 1, 2021 | I joined as an Assistant Professor at the Department of Computer Science, Hanyang University in the fall of 2021. |
Selected Publications
- CVPRMSTR: Mutli-Scale Transformer for End-to-End Human-Object Interaction DetectionIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022
- CVPRVideo-Text Representation Learning via Differentiable Weak Temporal AlignmentIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022
- ACLHypergraph Transformer: Weakly-supervised Multi-hop Reasoning for Knowledge-based Visual Question AnsweringIn In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics 2022
- EMNLPSemantic Alignment with Calibrated Similarity for Multilingual Sentence EmbeddingIn Findings of the Association for Computational Linguistics: EMNLP 2021 2021
- CVPRHOTR: End-to-End Human-Object Interaction Detection with TransformersIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021
- SciBulletinUnified deep learning model for El Niño/Southern Oscillation forecasts by incorporating seasonality in climate dataScience Bulletin 2021
- AAAIImage-to-Image Retrieval by Learning Similarity between Scene GraphsIn Proceedings of the AAAI Conference on Artificial Intelligence 2021
- CVPRHypergraph attention networks for multimodal learningIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020
- AAAICut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video DataIn Proceedings of the AAAI Conference on Artificial Intelligence 2020