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Generative Models for Visual Content Editing and Creation

  • Zheng WEI
  • , Xian XU
  • , Yuqing LIU
  • , Grace HAN
  • , Anyi RAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationProceedings - SIGGRAPH Asia 2025 Courses, SA Courses 2025
EditorsStephen N. Spencer, Taku Komura, Melina Skouras
PublisherAssociation for Computing Machinery, Inc
Number of pages3
ISBN (Electronic)9798400721311
DOIs
Publication statusPublished - 14 Dec 2025
EventSA Courses '25: SIGGRAPH Asia 2025 Courses - Hong Kong, Hong Kong, China
Duration: 15 Dec 202518 Dec 2025

Course

CourseSA Courses '25: SIGGRAPH Asia 2025 Courses
Country/TerritoryHong Kong, China
CityHong Kong
Period15/12/2518/12/25

Bibliographical note

Publisher Copyright:
© 2025 Copyright held by the owner/author(s).

Funding

We thank the CVEU workshop community (ICCV2021; ECCV2022; ICCV 2023; CVPR 2024, 2025; SIGGRAPH 2024 [Rao et al. 2024b], 2025 [Patashnik et al. 2025]), the 2025 HKUST AI Film Festival, and our colleagues at HKUST VisLab and the Multimedia Creativity Lab (MMLab).

Keywords

  • Generative AI
  • Diffusion Models
  • Pre-visualization
  • Storyboarding
  • Cinematic VR
  • Human-AI Collaboration
  • Responsible AI

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