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Coloring 3D Objects Using Generative AI
Pablo Wiedemann
Pablo Wiedemann
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Coloring 3D Objects Using Generative AI

Learn how to use modern AI image generators to color and stylize 3D objects through text prompts.

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Apply now
Tuesdays
 at
7:00
P.M.
 ET /
4:00
P.M.
PT
8 weeks, 2-3 hours per week
Intermediate
No experience required
No experience required
Some experience required
Degree and experience required

Description

Generative AI is currently one of the most in-demand skills across multiple industries. As this technology continues to spread across a wide range of fields, the demand for professionals with experience in generative AI is only expected to grow. An area of particular interest is the intersection of computer graphics and generative AI. Can we utilize generative AI to create/edit 3D content? This holds significant potential for industries such as video games, digital architecture, e-commerce, and AR/VR.

You'll wear the hat of a Junior Machine Learning Scientist and leverage generative AI models to enhance 3D digital objects. You will use advanced technologies like "ControlNet" and the "Segment Anything Model" to generate and apply new colors and textures to 3D models. You will also become familiar with industry-standard tools such as Google Colab, PyTorch, and Diffusers.

Session timeline

  • Applications open
    May 27, 2024
  • Application deadline
    June 23, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    July 8, 2024
  • Project end date
    Week of

What you will learn

  • Use Python to manipulate 3D objects and scenes
  • Use Hugging Face and PyTorch to run the latest ML models
  • Use Google Colab to perform ML experiments and share those with others
Build Projects are 8-week experiences that operate on a rolling basis. Selected participants engage in weekly live workshops with a Build Fellow and 2-15 other students.

Project workshops

1
Introduction
2
3D Object manipulation using Python
3
Introduction to ControlNet
4
ControlNet Part 2
5
Segment Anything Model
6
Image Super-Resolution
7
Consolidation and Cleanup
8
Presentations

Prerequisites

  • Good understanding of Python: you should be able to work with common data structures like lists, dictionaries, and sets; perform basic data and image manipulation and analysis using packages like NumPy and PIL.  
  • Basic knowledge of Machine Learning: you should understand ML concepts such as supervised and unsupervised learning, encoder/decoder, latent space, backpropagation, etc.  
  • Familiarity with PyTorch: You should know what a tensor is and how to manipulate it.  
  • Big plus: you have experience with computer graphics or 3D modeling tools. E.g. you have taken a course in computer graphics or related fields  
  • Other prerequisites: before the project starts, you'll need to have good internet connection to use Google Colab

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About the expert
Pablo Wiedemann
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Pablo
's Linkedin

Pablo is the co-founder and Chief Product Officer at Hypothetic Inc., a 3D Generative AI company. With over seven years of experience as a Machine Learning scientist he has worked on ML for Computer Animation, 3D Rendering, and Fluid Simulations, and founded three ML companies. He holds an MSc in Applied Mathematics.

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