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Animation & VFX · MS elective · 3 credit hours · 16 sessions

AI-Assisted Animation

This cutting-edge course integrates Artificial Intelligence into the traditional animation pipeline to accelerate production. Students will learn to use AI tools for markerless motion capture, automated lip-syncing, and generative texturing. The goal is not to replace the animator, but to use AI to handle repetitive tasks (clean-up, in-betweening) so the artist can focus on performance.

§ 01 By the end you can
  1. Utilize AI Motion Capture tools (e.g., Wonder Dynamics, Move.ai) to turn video into keyframes
  2. Automate Lip-Sync and facial animation using audio-driven AI
  3. Apply Style Transfer AI to render 3D scenes in 2D painterly styles
  4. Generate textures and background assets using diffusion models
  5. Navigate the ethics of AI, copyright, and the changing role of the animator
§ 02 Sixteen sessions

The whole semester.

  1. 01The AI Animation Pipeline: Overview
  2. 02Markerless Mocap: Video-to-Animation
  3. 03Cleaning AI Data: Retargeting & Polish
  4. 04AI Lip-Sync: Audio-Driven Facial Performance
  5. 05Generative In-Betweening (Frame Interpolation)
  6. 06Text-to-Motion: Prompting Movement
  7. 07AI Rigging: Auto-Rigging Tools (AccuRIG)
  8. 08 · MidtermMidterm Examination
  9. 09Generative Texturing & UVs
  10. 10AI Concept Art for Character Design
  11. 11Neural Rendering & NeRFs in Animation
  12. 12Style Transfer: Anime/Oil Paint Filters
  13. 13AI Physics assistance (Cascadeur)
  14. 14Rapid Prototyping/Animatics with AI
  15. 15Ethics: Deepfakes & Artist Rights
  16. 16Final Project: The Hybrid AI Short

Midterm around session 8. Final project briefed at session 8 or 9 and developed in stages until the juries.

§ 03 Final project

Final Project: The Hybrid AI Short

How it’s judged

Recommended reading
  1. Artificial Intelligence for Filmmakers (Industry Whitepapers)
  2. The Future of Animation by S. D. Katz
  3. Deep Learning for Computer Vision by Rajalingappaa Shanmugamani
  4. Generative Deep Learning by David Foster
  5. Online Documentation: Wonder Dynamics / RunwayML
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