@misc{foundrycopycatdune2casestudy,
  title = {Foundry CopyCat ML on Dune: Part Two (Production Case Study)},
  year = {2024},
  publisher = {Foundry},
  url = {https://www.foundry.com/insights/machine-learning/untapped-potential-ml-vfx},
  abstract = {Foundry's case study documents the use of CopyCat machine learning models in the compositing pipeline for Dune: Part Two, released in March 2024. Artist-trained models handled approximately 40 per cent of around 1,000 Fremen eye shots without manual touch-ups, using a training set of 280 shots from the first film augmented to 30,000 images. The explicit use of the production team's own data as training material is a notable provenance element, directly relevant to teaching discussions about responsible ML pipeline design. The case study is already in circulation among compositing educators by word of mouth; this is the primary vendor account.},
  keywords = {vfx-production, generative-ai, training-data, production-practice},
  note = {AI \& Animation Education Knowledge Base}
}