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Neural Radiance Fields (NeRF)

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    Thread Author
    VIP
    • Nov 2018 
    • 1307 
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    Published 12/2022
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.02 GB | Duration: 4h 51m
    Introduction to NeRF, volumetric rendering, and 3D reconstruction

    What you'll 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
    Requirements
    Basic programming knowledge
    Basic Machine Learning knowledge
    Description
    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 modelHow to extract a 3D mesh from an optimized modelHow to integrate Nerf into your computer vision projects Examples of real-world use cases for Nerf in the industryOur 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!
    Overview
    Section 1: Introduction
    Lecture 1 Introduction
    Lecture 2 Introduction to reconstruction - part 1
    Lecture 3 Introduction to reconstruction - part 2
    Section 2: 3D reconstruction
    Lecture 4 Ray tracing and Camera Model
    Lecture 5 Camera: visualization
    Lecture 6 3D rendering
    Lecture 7 Volumetric rendering - part 1
    Lecture 8 Volumetric rendering - part 2
    Lecture 9 Differentiable rendering & Optimization
    Lecture 10 Adding a rotation matrix to the camera: Camera To World
    Section 3: 3D reconstruction : modules
    Lecture 11 Camera and Dataset - part 1
    Lecture 12 Camera and Dataset - part 2
    Lecture 13 Volumetric Rendering
    Lecture 14 3D model: Voxels
    Lecture 15 Machine Learning Optimization loop
    Lecture 16 White background regularization
    Lecture 17 Mode collapse on synthetic data: solution
    Section 4: NeRF : Neural Radiance Fields
    Lecture 18 Introduction
    Lecture 19 Architecture: implementation
    Lecture 20 Positional encoding : implementation
    Lecture 21 Results
    To engineers and programmers,To entrepreneurs,To students and researchers

    Homepage
    https://www.udemy.com/course/neural-...e-fields-nerf/

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