Follow along with a practical 2D Pose estimation project using the latest papers and YouTube videos.

✅ People who don't know 2D pose estimation but want to study the latest papers and try setting up and developing the environment

✅ People who are tired of Object Detection projects and want to start a new project

✅ People who want to quickly apply a pose estimation model to projects such as graduation projects or competitions

✅ People who don't want to go through trial and error when starting pose estimation research

Introduction to 2D Pose Estimation → LitePose Paper Theory and Practice → DCPose Paper Theory and Practice → Custom Dataset Practice

Q. Can I take this course without any prior knowledge of pose estimation?

Yes! Even if you don't have a basic foundation, you don't have to worry because we'll walk you through how to run the code from start to finish. If you're simply interested in pose estimation, you can take this course. (However, you should have a basic understanding of deep learning and Python syntax !)

Q. What can I do if I learn pose estimation?

Pose estimation remains an active research area and is utilized across a wide range of industries. It currently underpins a variety of technologies, including drowsy driving detection, pose estimation in AR and VR environments, and coaching in the sports industry. The possibilities are endless!

• The course will be conducted in an Ubuntu environment equipped with GPU and CUDA development environments, as models are trained based on PyTorch and actual papers.
• This lecture was recorded using Linux and Ubuntu 20.04 . We recommend using a compatible environment.
• To practice implementing the model, you will need a PC with a graphics card .
• All source code used in the lectures is provided to students as learning materials.