Neural Radiance Fields (NeRF)

Introduction to NeRF, volumetric rendering, and 3D reconstruction

4.32 (111 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Introduction to reconstruction

Introduction to 3D reconstruction

Introduction to Neural Radiance Fields (NeRF)

Novel view synthesis with NeRF

3D reconstruction with NeRF (mesh extraction)

Introduction to 3D rendering

Why take this course?

Welcome to this course about Neural Radiance Fields (Nerf)!

Neural radiance fields is an innovative technology that is attracting a lot of interest in the world of computer vision. Nerf allows novel view synthesis, and 3D reconstruction, among other things. Since its appearance two years ago, many startups have been created, and as job offers suggest, large technology companies (Meta, Apple, Google, Amazon, ...) are using it.

In this online course, you will discover:

How Nerf models work and how they can be used in various applications
How to train and evaluate a Nerf model
How to generate novel views from an optimized model
How to extract a 3D mesh from an optimized model
How to integrate Nerf into your computer vision projects
Examples of real-world use cases for Nerf in the industry

Our course is designed for developers and scientists who want to learn about Nerf and use it in their projects. We cover all aspects of setting up and using Nerf, from start to finish.

Register now to access our comprehensive online course on Nerf models and learn how this technology can enhance your computer vision projects.

Don't miss this opportunity to learn about the latest advances in computer vision with Nerf!

Screenshots

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Reviews

Robert

September 24, 2023

It’s a bit distracting that he is altering/ debugging code. We all write like that but it’s unusual in a demo. Maybe it will grow on me. The over all presentation and content are very good so far

Rafael

September 16, 2023

great tutorial! i want more tutorials from this author and these topics! ranging from the background to create the application itself! i will buy more 3d tutorials with machine learning of this type and from this author, no doubt!

김서연

September 15, 2023

This course is perfect for who wants to implement raw NeRF model for studying, learning etc. It's really helpful and I wish to have more like this kind of courses too.

Shohei

July 4, 2023

The course is comprehensive, from explicit to neural implicit model optimization and some more advanced topics from more recent papers and tools. The videos sometimes go dull because the lecturer goes back and forth for debugging.

Alexander

July 3, 2023

This is a great introductory course on neural radiance fields (NeRFs). The author of the course delivers a good explanation of how the vanilla version of NeRF can be implemented including how performance can be improved using tiny-cuda-nn. It is a very good starting point for getting into NeRFs! My only suggestions for improving the course will be the following: - I suggest to reduce the section on papers to a list of publications with a short descriptions why you think every paper is important in your opinion. Short summary will make it easier to select which papers to read according to the interests of the student. - It will be interesting to see a section on how to implement instant-ngp like architecture. - If at some point you gonna redo your course, it will be good to reduce the amount of life debugging. It will provide a clearer and more concise delivery of the information. Good resource in recent publications for those who are interested in NeRFs =) : https://neuralradiancefields.io Thank you for your course!!!

Colin

June 30, 2023

I really liked this course. I felt it was a good way to help beginners become intermediate. The only thing I may add is for lectures and explaining what some things are I'd highly recommend something like a powerpoint. That way at the end of videos or paper reviews or code blocks you can talk about new things learned, helpful takeaways and more.

Darius

May 14, 2023

If you've taken intro classes to computer graphics and computer vision, this is the BEST resource on NeRF on the entire internet. He starts from the fundamental building blocks of NeRF and gradually builds up. E.g. He gave a great example to illustrate why volumetric rendering is used by NeRF (because it's differentiable and thus optimizable by auto-diff framework like PyTorch)

Mohamed

May 12, 2023

At the start of the course, I was surprised by the depth of knowledge presented by the instructor. He skillfully covered a wide range of topics, starting from the fundamentals and progressing to advanced concepts in both science and coding. I am truly grateful for the valuable insights gained from their teaching. Additionally, I would appreciate if he could provide an explanation of "BARF" (Bundle-Adjusting Neural Radiance Fields). I am eager to learn more about this particular technique. Thank you!

Yuvraj

March 26, 2023

This is all about coding. I was looking more about how do I put the images in a software and get a 3 model out of it

Somya

March 14, 2023

Very Good course!! I am eagerly waiting for it's next version in which many more things would be there.

Dharmendra

February 15, 2023

Great course, everything is clearly explained in 10 hours. But this course can be extended further by implementing the actual NeRF hierarchical sampling. Great explanation, very good content...... well done.....

Karthikeyu

February 8, 2023

Excellent course. I recommend this course to people who are interested in neural radiance fields. If point cloud extraction is included along with mesh that would be great and helpful for students.

Josiah

January 24, 2023

This is a great course. I would recommend to anyone looking to learn NeRF or just interested in this type of machine learning. The instructor approaches this well by first implementing using voxels then showing how this relates to NeRF and then implementing NeRF.

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