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stnoah1/README.md

๐Ÿ‘‹ Hi, I am Hyung-gun Chi (์ง€ํ˜•๊ทผ) <๐Ÿ |๐ŸŽ“|๐Ÿ“„>

I am a PhD student in Computer Engineering at Purdue University, advised by Professor Karthik Ramani. My research interests lie in Computer Vision, focusing on 3D Geometric Deep Learning and Action Analysis and their applications to AR/VR.

๐Ÿ“„ Selected Publications

  • W. Roh, S. Lee, W. Ryoo, G. Oh, J. Lee, S. Hwang, H. Chi, and S. Kim. Functional Hand Type Prior for 3D Hand Pose Estimation and Action Recognition from Egocentric View Monocular Videos. BMVC (Oral), 2023.
  • H. Chi, K. Lee, N. Agarwal, K. Ramani, and C. Choi. AdamsFormer for Spatial Action Localization in the Future. CVPR, 2023.
  • Y. Xu, A. Bazarjani, H. Chi, C. Choi, and Y. Fu. Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction. CVPR, 2023.
  • H. Chi*, S. Chi*, S. Chan, and Karthik Ramani. Pose Relation Transformer: Refine Occlusions for Human Pose Estimation. ICRA, 2023. [CODE]
  • H. Chi*, M. H. Ha*, S. Chi, S. Lee, Q. Huang, and Karthik Ramani. InfoGCN: Representation Learning for Human Skeleton-based Action Recognition. CVPR, 2022. [CODE]
  • H. Chi*, S. Kim*, X. Hu, Q. Huang, and Karthik Ramani. A Large-scale Annotated Mechanical Components Benchmark for Classification and Retrieval Tasks with Deep Neural Networks. ECCV, 2020. [CODE]
  • S. Kim, H. Chi, and Karthik Ramani. First-Person View Hand Segmentation of Multi-Modal Hand Activity Video Dataset. BMVC, 2020.

๐Ÿ’ป Skills

  • Language : Python, Matlab, C/C++, SQL, JavaScript, HTML, CSS, PHP
  • Machine/Deep Learning : PyTorch, TensorFlow, Keras
  • Web Programming : MYSQL/mongoDB, Flask/Node.js
  • CAD Tool : Creo Parametric, SolidWorks, AutoCAD

Pinned Loading

  1. infogcn infogcn Public

    Official implementation for "InfoGCN: Representation Learning for Human Skeleton-Based Action Recognition"

    Python 116 12

  2. mcb mcb Public

    A large-scale mechanical components benchmark for the classification and retrieval tasks named Mechanical Components Benchmark (MCB)

    HTML 49 4