Jang Mi's starred repositories
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
Solutions of Reinforcement Learning, An Introduction
librealsense
Intel® RealSense™ SDK
modern-cpp-features
A cheatsheet of modern C++ language and library features.
junior-recruit-scheduler
주니어 개발자 채용 정보
learnopencv
Learn OpenCV : C++ and Python Examples
visual-comet
VisualCOMET: Reasoning about the Dynamic Context of a Still Image
Sketch2Color-anime-translation
Given a simple anime line-art sketch the model outputs a decent colored anime image using Conditional-Generative Adversarial Networks (C-GANs) concept.
eye_blink_detector
Eye blink(Closeness-Openess) detection using CNN (Keras)
eye_blink_detection
eye blink detection
Reference-Based-Sketch-Image-Colorization-ImageNet
PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset
reference_based_sketch_image_colorization
PyTorch implementation of the paper "Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence" (CVPR 2020)
SplitFilling
"User-Guided Line Art Flat Filling with Split Filling Mechanism" in CVPR 2021
paper-to-code-Reference-Based-Sketch-Image-Colorization
논문 구현 및 실험 : Reference Based Sketch Image Colorization using Augmented Self Reference and Dense Semantic Correspondence
Reference_based_Skectch_Image_Colorization
This repository implements the paper "Reference based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence" which is published in CVPR2020.
Manga_Colorization
cGAN-based Manga Colorization Using a Single Training Image.
developer-roadmap-kr-
2020년, 웹개발자가 되기 위한 로드맵 https://roadmap.sh
Newbie-Guideline
컴퓨터과학/공학 신입생 및 비전공자 신입을 위한 지침서
Awesome-Image-Colorization
:books: A collection of Deep Learning based Image Colorization and Video Colorization papers.
MemoPainter-PyTorch
An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.