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JEONG HYEONJIN's Projects

alexnet icon alexnet

Implementation of AlexNet for Identifying that Wether first convolutional kernel's patterns are really bisected caused by it's parallel architecture

deep-high-resolution-net.pytorch icon deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

extrinsic2pyramid icon extrinsic2pyramid

Visualize Camera's Pose Using Extrinsic Parameter by Plotting Pyramid Model on 3D Space

git-tutorial icon git-tutorial

깃허브 관련해서 이것저것 실험해보는 쓰레기 Repository

gtsam icon gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

multical icon multical

Multi-camera calibration using one or more calibration patterns

neural_motion_project icon neural_motion_project

소수의 특징점을 가진 환경(VR 기기 등)에서 다수의 특징점을 신경망으로 예측해 Full Body Tracking하는 것을 목표로 하는 기업외주과제

okvis icon okvis

OKVIS: Open Keyframe-based Visual-Inertial SLAM.

okvis_ros icon okvis_ros

OKVIS: Open Keyframe-based Visual-Inertial SLAM (ROS Version)

pixel-cnn icon pixel-cnn

Code for the paper "PixelCNN++: A PixelCNN Implementation with Discretized Logistic Mixture Likelihood and Other Modifications"

pymo icon pymo

A library for machine learning research on motion capture data

real-time-human-pose-estimation-by-pytorch icon real-time-human-pose-estimation-by-pytorch

A reimplementation of real time human pose estimation using Pytorch. Both CMU's original model and mobilenet backbone are provided. The code is optimized for a faster inference time !

residualnet icon residualnet

Implementation of ResidualNet on CIFAR-10 dataset. test model with various option(bottleneck block, projection shortcut) (모델변형 간의 성능비교)

sophus icon sophus

C++ implementation of Lie Groups using Eigen.

tensorrt icon tensorrt

TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.

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