Generative Models for Visual Content Editing and Creation
Zheng Wei, Xian Xu, Yuqing Liu, Grace Han, Anyi Rao · 2025
Generative AI now drives storyboarding, previs, and look-development, yet two gaps slow adoption: artists struggle with opaque tools, while ML engineers lack cinematic grammar. This half-day master class closes both gaps by pairing concise theory with hands-on, human-in-the-loop practice and built-in ethics. Through an Explain → Show → Do rhythm, each concept moves from a crisp technical snapshot to a live demo and a guided task. Team exercises turn peer critique into a rapid feedback loop, while questions of authorship, bias, and legal clearance surface at every step—embedding responsible practice into real production workflows. Live demos built on the CineVision pipeline transform a log-line into reference frames, shot lists, and colour-graded contact sheets, showcasing diffusion, LoRA, ControlNet, AnimateDiff, and IP-Adapter in action. Participants leave able to (i) explain how modern diffusion and multimodal generators work, (ii) customise tool-chains without ceding creative control, (iii) integrate AI assets into coherent, ethically sound sequences, and (iv) assess—and build—production-ready pipelines that enhance director–cinematographer collaboration.