Affine / perspective transformation in Pose Estimation with Tensorflow 2

Overview

Pose Transformation

Affine / Perspective transformation in Pose Estimation with Tensorflow 2

Introduction

이 repo는 pose estimation을 연구하고 개발하는 데 도움이 되기 위해 만들었다.
딥러닝 모델을 학습시키기 위해서는 입력값을 모델의 산출물과 비교 가능하도록 변환해야 하며, 이는 수학적 이론에 근거하고 있다.
코드와 이론이 분명 존재하지만, 이를 비교해가며 유기적으로 연관지어 구현한 자료를 찾기 어렵고,
있다고 하더라도 대부분이 opencv로 구현된 모듈을 가져다가 활용하는 것이 대부분이다.
그래서 이러한 갈증을 해소하기위해 선형대수의 내용과 이를 코드로 구현할 예정이며, Tensorflow를 사용한다.

This repo was created to help you research and develop pose estimation. In order to train a deep learning model, it is necessary to transform the input value so that it can be compared with the output of the model, which is based on mathematical theory. Codes and theories clearly exist, but it is difficult to find materials that are organically related and implemented by comparing them. Even if there is, most of it is to take a module implemented with opencv and use it. So, to satisfy this thirst, we plan to implement the contents of linear algebra in code using Tensorflow 2.

Contents

  • 2D single-pose: cropped object as an input
  • 2D single-pose: whole image as an input
  • 2D multi-pose

Requirements

Demo

References

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