Rodin: Roll-out Diffusion Network
This article covers the Rodin diffusion model for creating 3D avatars from neyral radiance fields (NeRFs).
a year ago
Tabitha Oanda
I am currently a research fellow at Paperspace on the Advanced Technologies Group
NARF: Neural Articulated Radiance Fields
In this article, we take a deeper look at Neural Articulated Radiance Fields, and examine their potential for 3d modeling.
a year ago
3D-Aware Generation using 2D Diffusion Models
In this article, we continue our look at the theory behind recent works on transferring the capabilities of 2D diffusion models to create 3D-Aware Generative Diffusion models.
a year ago
Inverting Images in Generative Models: An Overview
In this blog post, we take a deeper look at the inversion techniques utilized by GANs to embed features and then manipulate them in the latent space,
2 years ago
Exploring and Exploiting the Latent Style Space
In this article we look at the Style Space in StyleGAN models - a way for us to understand and identify style channels that control both local semantic regions and specific attributes defined by positive samples
2 years ago
The Evolution of StyleGAN: Introduction
This article reviews the development of the influential StyleGAN model throughout its development history.
2 years ago
3D Generation Deep Learning Models
In this article, we take a look at several useful tools for generating fast, high quality 3D images with Python.
2 years ago
Using Diffusion Models for Image Editing Tasks
In this blog post, we review recent diffusion models that have been used not only for generic image generation but also for image editing purposes. Within, we go go over each model and summarize the blog post with the pros and cons of each model.
2 years ago
Analyzing the Power of CLIP for Image Representation in Computer Vision
In this article, we examine typical computer vision analysis techniques in comparison with the modern CLIP (Contrastive Language-Image Pre-Training) model.
2 years ago
