Efficient Geometry-Aware 3D Generative Adversarial Networks - GAN Paper Explained
Offered By: Aleksa Gordić - The AI Epiphany via YouTube
Course Description
Overview
Dive into a comprehensive video explanation of the "Efficient Geometry-aware 3D Generative Adversarial Networks" paper, exploring a novel explicit-implicit 3D scene representation network and its framework for state-of-the-art 3D GANs. Learn about NeRF, tri-plane 3D scene representation, efficient 3D GANs pipeline, dual discrimination, and super-resolution techniques. Examine the results, ethical considerations, and robustness of intrinsics and extrinsics in this cutting-edge approach to 3D generative models.
Syllabus
Intro
Tri-plane 3D scene representation intro
NeRF in depth
Explicit voxel grid methods
Tri-plane 3D scene representation explained
Tri-plane is as expressive
Efficient 3D GANs pipeline
Pose correlated facial features
Dual discrimination, super-resolution
Results
Ethical considerations, are we going to change anything?
Intrinsics, extrinsics robustness?
Outro
Taught by
Aleksa Gordić - The AI Epiphany
Related Courses
Sparse Representations in Image Processing: From Theory to PracticeTechnion - Israel Institute of Technology via edX Cutting Edge Deep Learning for Coders
Jeremy Howard via YouTube Beyond Text - Giving Stable Diffusion New Abilities
HuggingFace via YouTube Single Image Super Resolution Using SRGAN
DigitalSreeni via YouTube New Approaches to Image and Video Reconstruction Using Deep Learning
Meta via YouTube