|
Hank Chi-Hsi Kung 孔啟熙 I am a visiting researcher at Indiana University Bloomington where I am working with Prof. David Crandall and Prof. Linda Smith. My current research focuses on visual representation learning in both human and machine intelligence Previously, I was a research assistant at National Chiao Tung University, Taiwan, and was supervised by Prof. Yi-Ting Chen and Dr. Yi-Hsuan Tsai. I was a research intern at IBM Thomas J. Watson Research Center. I received my M.Sc from National Tsing-Hua University, where I was supervised by Prof. Che-Rung Lee, and B.Sc from National Taipei University. I am actively seeking a Ph.D. position! Email / Google Scholar / X / Github / CV |
|
Research InterestsI am interested in developing Human-Like AI that can rapidly adapt and generalize from limited data or experience by reusing learned concepts and composing new ones. A promising approach to reverse-engineering human cognition is to identify its key ingredients by leveraging insights from cognitive science and developmental psychology—how do humans learn? To make progress in this direction, my research focuses on:
|
Workshop OrganizingOrganizing Reverse-Engineering Human Learning Mechanisms: Toward Human-Like AI at NeurIPS 2025 3rd ROAD++ Workshop & Challenge of Compositional Representation for Traffic Activities at ECCV 2024 |
Publications |
|
|
Learning to Look Like Humans: Modeling Planar View Bias Development with Offline Reinforcement Learning
Chi-Hsi Kung, Frangil Ramirez, Juhyung Ha, Alfredo Pereira, Yi-Ting Chen, David Crandall, Linda Smith |
|
What Changed and What Could Have Changed? State-Change Counterfactuals for Procedure-Aware Video Representation Learning
Chi-Hsi Kung*, Frangil Ramirez*, Juhyung Ha, Yi-Ting Chen, David Crandall, Yi-Hsuan Tsai, (* Equal Contribution) Under review arxiv / Code coming soon |
|
ATARS: An Aerial Traffic Atomic Activity Recognition and Temporal Segmentation Dataset
Zihao Chen, Hsuanyu Wu, Chi-Hsi Kung*, Yi-Ting Chen*, Yan-Tsung Peng* (* Equal Advising) Under review arxiv / Code / |
|
Controllable Scenario-based Collision Generation for Safety Assessment
Pin-Lun Chen, Chi-Hsi Kung, Che-Han Chang, Wei-Chen Chiu, Yi-Ting Chen Under review Paper coming soon / Code coming soon |
|
Action-slot: Visual Action-centric Representations for Atomic Activity Recognition in Traffic Scenes
Chi-Hsi Kung, Shu-Wei Lu, Yi-Hsuan Tsai, Yi-Ting Chen CVPR, 2024 project page / paper / arxiv / code / TACO dataset |
|
RiskBench: A Scenario-based Benchmark for Risk Identification
Chi-Hsi Kung, Chieh-Chi Yang, Pang-Yuan Pao, Shu-Wei Lu, Pin-Lun Chen, Hsin-Cheng Lu, Yi-Ting Chen ICRA, 2024 project page / video / paper / code / dataset |
|
ADD: A Fine-grained Dynamic Inference Architecture for Semantic Image Segmentation
Chi-Hsi Kung and Che-Rung Lee IROS, 2021 & ACML 2021 MRVC workshop paper / code |
Conference ReviewerIEEE Conference on Computer Vision and Pattern Recognition CVPR 2023-2025 The International Conference on Machine Learning ICML 2025 International Conference on Computer Vision ICCV 2025 Advances in Neural Information Processing Systems NeurIPS 2024 IEEE International Conference on Development and Learning ICDL 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems IROS 2025 |
Invited Talk |
|
Feel free to steal this website's source code. Do not scrape the HTML from this page itself, as it includes analytics tags that you do not want on your own website — use the github code instead. Also, consider using Leonid Keselman's Jekyll fork of this page. |