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👋 indigo / @indigopyj / Yeo Jeong Park

🔨 Career

  • Research Engineer in KT AI2XL, Large Vision AI TF (2023.09 ~ )
  • Research Intern in Naver Search, Vision (2020.07 ~ 2020.09)
  • Bachelor Intern in Seoul Nat'l Univ. Machine Intelligence & Pattern Recognition Lab (2020.01 ~ 2020.02)

📝 Education

  • M.S Degree in KAIST Data and Visual Analytics(DAVIAN) Lab (2021.09 ~ 2023.08)
  • B.S in Computer Engineering, Ewha Womans University (2016.03 ~ 2021.02)
  • Exchange Student in Technische Universitat Darmstadt, Germany (2018.02 ~ 2019.02)

💚 Interests

  • Computer Vision, Generative Model, Model compression, Knowledge Distillation, Efficient Deep Learning

Yeojeong Park's Projects

android_camera2_api_video_app icon android_camera2_api_video_app

Code for the android tutorial series found here https://www.youtube.com/playlist?list=PL9jCwTXYWjDIHNEGtsRdCTk79I9-95TbJ that describes how to create an android video application using the android camera2 API.

clustering icon clustering

Implements "Clustering a Million Faces by Identity"

colorization icon colorization

Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.

convmesh icon convmesh

Code for "Convolutional Generation of Textured 3D Meshes", NeurIPS 2020

deepgaze icon deepgaze

Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.

dlib icon dlib

A toolkit for making real world machine learning and data analysis applications in C++

fixmatch-pytorch icon fixmatch-pytorch

Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"

gan-compression icon gan-compression

[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs

ict_coc_hackathon icon ict_coc_hackathon

This code is for ICT_Coc_Hackathon. The goal is detecting the defect of sewer pipe from the pictures taken by CCTV

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