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Hoya012's Research Blog

About Ho Seong Lee

  • I received the B.S. degrees, in Electrical and Computer Engineering from Seoul National University, Seoul, Korea, in 2016.
  • I received theM.S. degrees, in Electrical and Computer Engineering from Seoul National University, Seoul, Korea, in 2018.
  • In 2018, I joined theSUALAB.,Seoul, Korea, as a Machine Learning Engineer.
  • My research interests include algorithm and architecture for image recognition, image processing using deep learning.
  • I'm organizer ofSNUAI study, TFUG(TensorFlow-KR Facebook User Group)
  • I participates inPR-12 Deep Learning Paper Reading Study from Tensorflow-KR Facebook User Group.

    • Repository

  • https://github.com/hoya012/swa-tutorials-pytorch
  • https://github.com/hoya012/NeurIPS-2020-Paper-Statistics
  • https://github.com/hoya012/automatic-mixed-precision-tutorials-pytorch
  • https://github.com/hoya012/semantic-segmentation-tutorial-pytorch
  • https://github.com/hoya012/carrier-of-tricks-for-classification-pytorch
  • https://github.com/hoya012/CVPR-2020-Paper-Statistics
  • https://github.com/hoya012/AAAI-2020-Paper-Statistics
  • https://github.com/hoya012/NeurIPS-2019-Paper-Statistics
  • https://github.com/hoya012/ICCV-2019-Paper-Statistics
  • https://github.com/hoya012/CVPR-2019-Paper-Statistics
  • https://github.com/hoya012/deep_learning_object_detection
  • https://github.com/hoya012/awesome-anomaly-detection
  • https://github.com/hoya012/fast-style-transfer-tutorial-pytorch
  • https://github.com/hoya012/shake-shake-tensorflow
  • https://github.com/hoya012/pytorch-densenet
  • https://github.com/hoya012/pytorch-peleenet
  • https://github.com/hoya012/pytorch-Xception
  • https://github.com/hoya012/pytorch-MobileNet
  • https://github.com/hoya012/pytorch-partial-conv-based-padding

    • Slides

  • "Unsupervised anomaly detection using style distillation" Paper Review
  • "Do Adversarially Robust ImageNet Models Transfer Better?" Paper Review
  • "CNN Architecture 톺아보기"
  • "Carrier of Tricks for Image Classification"
  • "The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization" Paper Review
  • "Mixed Precision Training" Paper Review
  • "MVTec AD: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection" Paper Review
  • "YOLOv4: optimal speed and accuracy of object detection" Paper Review
  • "FixMatch:simplifying semi supervised learning with consistency and confidence" Paper Review
  • "Revisiting self supervised visual representation learning" Paper Review
  • "Unsupervised visual representation learning overview: Toward Self-Supervision"
  • "Human uncertainty makes classification more robust, ICCV 2019 Review"
  • "Single Image Super Resolution Overview"
  • "2019 ICLR Best Paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" Review"
  • "2019 CVPR Paper Statistics & Paper Review"
  • "Pelee: a real time object detection system on mobile devices, 2018 NeurIPS" Paper Review
  • "How does batch normalization help optimization, 2018 NeurIPS" Paper Review
  • "Simple Does It: weakly supervised instance and semantic segmentation, 2017 CVPR" Paper Review
  • "From image level to pixel-level labeling with convolutional networks, 2015 CVPR" Paper Review
  • "Dataset and metrics for predicting local visible differences, 2018 SIGGRAPH" Paper Review
  • "Learning From Noisy Large-Scale Datasets With Minimal Supervision, 2017 CVPR" Paper Review
  • "Learning transferable architectures for scalable image recognition, 2018 CVPR" Paper Review
  • "Searching for Activation Functions, 2018 ICLR" Paper Review
  • "Google Vizier: A Service for Black-Box Optimization, 2017 KDD" Paper Review

    • Presentation

  • PR-290: Do Adversarially Robust ImageNet Models Transfer Better?
  • 서울대학교 머신러닝/딥러닝 학회 Deepest 초청 세미나, 2020.11.07
  • 카카오브레인 초청 세미나 (비대면), 2020.11.03
  • 서울과학기술대학교 전기정보공학세미나 특강(비대면), 2020.10.05
  • 비전을 나누는 시간(전액 기부 웨비나) 연사, 2020.9.18
  • [DevC Seongnam Launching] World of PyTorch - Invited Talk, 2020.9.17
  • PR-273: Mixed Precision Training
  • 고려대학교 산업경영공학부 산업인공지능 프로그램 - Invited Talk, 2020.8.11
  • PR-263: MVTec AD-A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
  • PR-249: YOLOv4: Optimal Speed and Accuracy of Object Detection
  • PR-237: FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
  • PR-222: Revisiting Self-Supervised Visual Representation Learning
  • PR-208: Unsupervised Visual Representation Learning Overview:Toward Self-Supervision
  • 제 9회 투빅스 빅데이터 컨퍼런스 - Invited Talk, 2020.1.11

    • Teaching Experience

  • Image Classification & Object Detection Overview in CUBOX, 2021.1 ~ 2021.3
  • Lecturer ofObject Detection Workshop, in FastCampus, 2018.10 ~ 2019.5
  • TA of Digital System Design and Experiments(디지털 시스템 설계 및 실습), in SNUECE(서울대학교 전기정보공학부), 2017.9 ~ 2017.12
  • TA of Digital System Design and Experiments(디지털 시스템 설계 및 실습), in SNUECE(서울대학교 전기정보공학부), 2016.9 ~ 2016.12

    • Publications

  • Taeoh Kim*, Hyeongmin Lee*, MyeongAh Cho*,Ho Seong Lee, Dong Heon Cho, Sangyoun Lee (*Equal Contribution), "Learning Temporally Invariant and Localizable Feature via Data Augmentation for Video Recognition," European Conference on Computer Vision Workshop (ECCVW 2020), July. 2020. </li>
  • Donghyeon Lee,Ho Seong Lee, Sangheon Lee, Kyujoong Lee, and Hyuk-Jae Lee, "Hardware Design of a Context-Preserving Filter-Reorganized CNN for Super-resolution," IEEE Journal on Emerging and Selected Topics in Circuits and Systems(JETCAS), Volume: 9, Issue: 4, Pages: 612-622, Dec. 2019.
  • Donghyeon Lee, Sangheon Lee,Ho Seong Lee, Kyujoong Lee, and Hyuk-Jae Lee, “Resolution-Preserving Generative Adversarial Networks for Image Enhancement," IEEE Access, Volume: 7, Pages: 110344-110357, Aug. 2019.
  • Donghyeon Lee, Sangheon Lee,Ho Seong Lee, Kyujoong Lee, and Hyuk-Jae Lee, “Context-Preserving Filter Reorganization for VDSR-Based Super-resolution," IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Mar. 2019.
  • 이호성, "CNN 및 Edge detection 기반고속 손 동작 인식", 서울대학교 전기정보공학부 석사학위논문(Thesis), Feb. 2018
  • Ho Seong Lee, Donghyeon Lee, Jinsung Kim, and Hyuk-Jae Lee, "Fast Hand Gesture Recognition with CNN and Feature Matching", 30th Workshop on Image Processing and Image Understanding, Feb. 2018 (Best Paper)
  • 이호성, 이동현, 김진성, 이혁재, “임베디드 보드 환경에서의 효율적인 손 인식 및 추적 방법에 대한 연구”, 제25회 한국반도체학술대회, Feb. 2018
  • Donghyeon Lee,Ho Seong Lee, Kyujoong Lee, and Hyuk-Jae Lee, "Super-Resolution을 위한 Deconvolution 적용 고속 컨볼루션 뉴럴 네트워크," 한국멀티미디어학회 논문지, Volume: 20, Issue: 11, Pages: 1750-1758, Nov. 2017.
  • 이호성, 이동현, 이규중, 이혁재, “CNN 알고리즘의 하드웨어 구현을 위한 고정 소수점 모델 구현 및 성능 분석,” 2017년도 대한전자공학회 하계종합학술대회, June. 2017
  • Donghyeon Lee,Ho Seong Lee, Hyun Kim, Jin-Sung Kim, and Hyuk-Jae Lee, “An Evenly Distributed Points based Hand Tracking Method,” International Technical Conference on Circuits/Systems, Computers and Communications, July. 2017
  • 이호성, 이동현, 김진성, 이혁재, "Markov Model 기반 손 제스처 인식 알고리즘", SoC 학술대회, May, 2017

    • Contact Me

    If you have questions about the post, feel free toemail me or create an issue onGitHub. Enjoy!



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