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Chi-Hsi Hank Kung I am a research assistant at National Yang Ming Chiao Tung University in Taiwan, where I work on visual action recognition and event identification in traffic scenes and advised by Prof. Yi-Ting Chen. Meanwhile, I am also actively collaborating with Dr. Yi-Hsuan Tsai. This summer, I will be visiting Indiana University Bloomington to delve into the intersection of egocentric vision and cognitive science with Prof. David Crandall. Prior to this, 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 looking for a Ph.D position for Fall 2025! Email / Google Scholar / Twitter / Github |
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ResearchMy research interest lies in video understanding, particularly action/behavior analysis for development of autonomous driving and long-horizon robot tasks. My current research topics focus on learning ego-centric and action-centric representations for recognition and temporal action segmentation in traffic scenes and daily-life activities. |
News |
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Apr 2024 |
Co-organizing the 3rd ROAD Workshop & Challenge at ECCV 2024! |
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Mar 2024 |
One paper on Visual Action-centric Representation is accepted at CVPR 2024! |
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Feb 2024 |
One paper on Risk Identification is accepted at ICRA 2024! |
Publications |
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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 / code / TACO dataset We use Action-slot to represent atomic activities. The learned attention can discover and localize atomic activities with only weak video labels and without using any perception module (e.g., object detector). |
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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 The FIRST benchmark that enables evaluation of various types of risk identification algorithms, namely, rule-based, trajectoy-prediction-based, collision prediction, and behavior-change-based. We also assess the influence of risk identification to the downstream driving task. |
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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 We use Neural Architecture Search (NAS) to find an optimal structure for dynamic inference on semantic segmentation. |
Conference ReviewerIEEE Conference on Computer Vision and Pattern Recognition (2023-2024) IEEE International Conference on Development and Learning (2024) |
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