Publications

2024

  1. Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks
    Hunmin Yang, Jongoh Jeong, and Kuk-Jin Yoon
    European Conference on Computer Vision (ECCV), 2024
    Oral Presentation
    Paper Project Page
  2. Object-Centric Domain Randomization for 3D Shape Reconstruction in the Wild
    Junhyeong Cho, Kim Youwang,  Hunmin Yang, and Tae-Hyun Oh
    arXiv preprint, 2024
    CVPR Workshop on Foundation Models (WFM), 2024
    Paper Project Page
  3. FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
    Hunmin Yang*, Jongoh Jeong*, and Kuk-Jin Yoon (*equal contribution)
    Association for the Advancement of Artificial Intelligence (AAAI), 2024
    ICCV Workshop on Adversarial Robustness In the Real World (AROW), 2023
    Paper Project Page

2023

  1. PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
    Junhyeong Cho, Gilhyun Nam, Sungyeon Kim,  Hunmin Yang, and Suha Kwak
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    Paper Project Page
  2. ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion
    Naufal Suryanto, Yongsu Kim, Harashta Tatimma Larasati, Hyoeun Kang, Thi-Thu-Huong Le, Yoonyoung Hong,  Hunmin Yang, Se-Yoon Oh, and Howon Kim
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    Paper Project Page
  3. Synthetic Image Generation for Deep Neural Networks
    Hunmin Yang, Se-Yoon Oh, and Junhyeong Cho
    NVIDIA GPU Technology Conference (GTC), 2023
    Spotlight Presentation
    Project Page
  4. Simulation of Physical Adversarial Attacks on Vehicle Detection Models
    Se-Yoon Oh, and Hunmin Yang
    International Conference on Control, Automation and Systems (ICCAS), 2023
    Paper

2022

  1. DTA: Physical Camouflage Attacks Using Differentiable Transformation Network
    Naufal Suryanto, Yongsu Kim, Hyoeun Kang, Harashta Tatimma Larasati, Youngyeo Yun, Thi-Thu-Huong Le,  Hunmin Yang, Se-Yoon Oh, and Howon Kim
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    Paper Project Page

2021

  1. Camouflaged Adversarial Attack on Object Detector
    Jeonghun Kim, Kyungmin Lee, Hyeongkeun Lee,  Hunmin Yang, and Se-Yoon Oh
    International Conference on Control, Automation and Systems (ICCAS), 2021
    Paper

2020

  1. D-GEN: A Deep Learning Data Generation Framework for Artificial Intelligence
    Hunmin Yang, Se-Yoon Oh, Taewon Kim, and Ki-Jung Ryu
    NVIDIA GPU Technology Conference (GTC), 2020
    Poster
  2. Training Deep Neural Networks with Synthetic Data for Off-Road Vehicle Detection
    Eunchong Kim, Kanghyun Park,  Hunmin Yang, and Se-Yoon Oh
    International Conference on Control, Automation and Systems (ICCAS), 2020
    Paper
  3. Improving Instance Segmentation using Synthetic Data with Artificial Distractors
    Kanghyun Park, Hyeongkeun Lee,  Hunmin Yang, and Se-Yoon Oh
    International Conference on Control, Automation and Systems (ICCAS), 2020
    Paper
  4. Adversarial training on joint energy based model for robust classification and out-of-distribution detection
    Kyungmin Lee,  Hunmin Yang, and Se-Yoon Oh
    International Conference on Control, Automation and Systems (ICCAS), 2020
    Paper
  5. Applying FastPhotoStyle to synthetic data for military vehicle detection
    Hyeongkeun Lee, Kyungmin Lee,  Hunmin Yang, and Se-Yoon Oh
    International Conference on Control, Automation and Systems (ICCAS), 2020
    Paper

2019

  1. Accelerating Distributed Deep Learning Inference on multi-GPU with Hadoop-Spark
    Hunmin Yang, Se-Yoon Oh, and Ki-Jung Ryu
    NVIDIA GPU Technology Conference (GTC), 2019
    Oral Presentation
    Project Page
  2. Scalable Distributed Deep Learning Inference on multi-GPU with Hadoop-Spark
    Hunmin Yang, Ki-Jung Ryu, and Se-Yoon Oh
    NVIDIA GPU Technology Conference (GTC), 2019
    Poster
  3. Optimal Distributed Inference on Multi-GPU Processing System
    Se-Yoon Oh,  Hunmin Yang, and Ki-Jung Ryu
    NVIDIA GPU Technology Conference (GTC), 2019
    Poster