Generative AI for Film Creation: A Survey of Recent Advances

2025-04-11

AI Summary

This study addresses three core challenges hindering generative AI adoption in film production—character inconsistency, stylistic discontinuity, and motion discontinuity—by proposing the first GenAI technology adoption framework tailored for cinematic workflows. Methodologically, it integrates text-to-image/video diffusion models, Neural Radiance Fields (NeRF), AI-driven avatar generation, 3D synthesis, and multimodal editing techniques to systematically investigate character generation, stylized expression, narrative construction, and live-action–AI content integration. Through empirical artist interviews, key improvement priorities—including controllability, fine-grained editing, and motion optimization—are identified. The primary contributions are: (1) a reusable AI-augmented filmmaking paradigm; (2) a bidirectional roadmap co-evolving technical advancement and artistic practice; and (3) a conceptual shift from AI-as-tool to AI-as-collaborative agent in creative filmmaking.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Computer Vision: Generative Adversarial Networks (GANs) for Vision
• Natural Language Processing: Generation

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D synthesis. This paper examines the adoption of these technologies in filmmaking, analyzing workflows from recent AI-driven films to understand how GenAI contributes to character creation, aesthetic styling, and narration. We explore key strategies for maintaining character consistency, achieving stylistic coherence, and ensuring motion continuity. Additionally, we highlight emerging trends such as the growing use of 3D generation and the integration of real footage with AI-generated elements. Beyond technical advancements, we examine how GenAI is enabling new artistic expressions, from generating hard-to-shoot footage to dreamlike diffusion-based morphing effects, abstract visuals, and unworldly objects. We also gather artists' feedback on challenges and desired improvements, including consistency, controllability, fine-grained editing, and motion refinement. Our study provides insights into the evolving intersection of AI and filmmaking, offering a roadmap for researchers and artists navigating this rapidly expanding field.

Problem

• Examining GenAI adoption in filmmaking workflows and contributions
• Exploring strategies for character consistency and stylistic coherence
• Addressing artists' challenges in controllability and fine-grained editing

Innovation

• Text-to-image and image-to-video diffusion
• Neural radiance fields for 3D synthesis
• AI-generated elements integration with real footage