This tutorial from Trelis Research provides a comprehensive guide to creating and fine-tuning AI avatar videos using advanced vision models. Learn the complete pipeline from basic concepts to implementation, starting with an introduction to AI avatars and simple avatar creation workflows. Explore the fundamentals of image diffusion, the transition to video diffusion techniques, and how to implement the MEMO model for realistic avatar generation. Follow along with detailed environment setup instructions, practical demonstrations of running inference, and step-by-step fine-tuning processes. The one-hour tutorial covers technical aspects including training configuration details, video pre-processing requirements, executing fine-tuning scripts, and analyzing results. Access additional resources including GitHub repositories, slides, and collaboration opportunities to enhance your AI avatar development skills. Perfect for developers looking to create personalized, high-quality AI-generated video avatars with custom training data.
Overview
Syllabus
00:00 Introduction to AI Avatars
00:23 Simple Avatar Pipeline
02:13 Understanding Image Diffusion
04:37 From Image to Video Diffusion
07:48 Implementing the MEMO Model
14:03 Setting Up the Environment
19:20 Running Inference and Fine-Tuning
34:30 Introduction to AI Avatar Creation
35:09 Initial Model Evaluation
36:00 Understanding Fine Tuning
36:54 Setting Up Fine Tuning
37:35 Training Configuration Details
44:23 Video Pre-processing
49:45 Running Fine Tuning Scripts
56:11 Analyzing Fine Tuning Results
01:01:32 Conclusion and Recommendations
Taught by
Trelis Research
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