AI in VFX: A Tool for Empowerment, Not Replacement

As a VFX professional deeply involved in the integration of AI technologies, I've observed firsthand how these tools are reshaping our industry. The transformation has been remarkable, yet one thing remains clear: AI is augmenting, not replacing, human creativity. Moreover, the cost savings brought about by AI have opened up new markets and opportunities for VFX studios, allowing them to expand their reach and cater to a broader range of clients.

From my perspective here are the key ways AI is revolutionizing VFX production:

🎥 Boosting Efficiency for Artists

AI tools like Meta's Segment Anything (SAM2) and Vitte-Matte are changing how we approach rotoscoping and matte extraction. While SAM2's segmentation isn't yet precise enough for final rotoscoping, it excels at creating quick garbage mattes and provides a solid foundation for trimatte workflows. As AI technology advances, I expect to see improvements in handling soft edges and motion blur - key challenges in current AI-based rotoscoping. Additionally, tools like NVIDIA OptiX accelerate ray tracing and rendering, while Beeble's normal map generation helps artists quickly create detailed surface information. By streamlining these technical steps, artists can focus more time on the creative aspects and less on button pushing.

🎨 Speeding Up Compositing

While compositing remains one of the most challenging areas for AI assistance due to its non-procedural nature, image-to-video (i2v) workflows can help compositors visualize the final result earlier in the process. These AI tools allow artists to quickly generate previews of how a comp might look, helping secure creative direction and identify potential issues before investing significant time in detailed comp work.

🖼️ AI as a Renderer

My research at TCL has uncovered AI as a renderer - by leveraging ComfyUI's node-based workflow and SDXL's innovative architecture, we achieved near-instant photorealistic results. SDXL's separation of style and composition into distinct components within the UNet allows unprecedented control over each aspect independently. This architectural choice enables artists to maintain consistent style across shots while freely adjusting composition, or vice versa. By combining this with normal maps, depth information, and IP-adaptor techniques, we can ensure shot-to-shot consistency while dramatically reducing render times compared to traditional methods. The system's ability to independently tune style and composition, while preserving visual continuity across sequences, delivers the high-quality output expected in professional VFX work. While this AI-powered approach complements rather than replaces traditional rendering pipelines, it represents a significant leap forward in rapid visualization and creative control.

📋 The Layout Step is Still Critical

The layout step remains a non-negotiable part of the VFX pipeline, especially when integrating AI-generated content. Whether matching camera moves for live action plates, maintaining consistent digital cinematography across shots, or ensuring proper spatial relationships between elements, there's simply no way to skip the layout phase. This foundational step gives artists and directors precise control over scene composition, camera work, and timing - critical aspects that AI tools currently cannot handle autonomously.

🎭 AI-Only Content Can't Replace Real Stories

While AI can generate stunning visuals, it remains fundamentally a brush in the filmmaker's/artist's toolkit and does not replace the artist themselves. No amount of AI-generated content can replace the cultural resonance that comes from real screenwriters drawing on lived experiences, or the nuanced performances of actors who breathe life into characters. These human elements - the writer's understanding of societal themes, the actor's ability to convey subtle emotions, the collaborative refinement of all aspects - are what transform impressive visuals into meaningful stories that resonate across cultures and generations. AI may help us paint more efficiently, but the artistic vision and emotional core of filmmaking remain deeply human endeavors.

💡 Training Materials

The debate around training materials and copyright is complex but ultimately moot - large language models and image generators trained on copyrighted works are already in widespread commercial use. Just as traditional tools can be used to either create original works or infringe on existing ones, AI is simply another brush in the artist's toolkit. The key distinction lies not in the tool itself, but in how we choose to use it. Forward-thinking studios are focusing on leveraging AI to create novel content while respecting intellectual property rights, just as they've always done with traditional tools.

🎞️ The 8-bit Limitation

A significant challenge in current AI tools for VFX is their reliance on 8-bit training data and limited color gamuts. While these constraints may be sufficient for consumer applications and social media content, professional VFX workflows demand higher precision. The limited color depth of 8-bit systems (256 values per channel) can lead to visible banding, reduced flexibility in color grading, and loss of subtle details in highlights and shadows - issues that are unacceptable in high-end production. Additionally, AI models typically output images in consumer color spaces like sRGB or Rec.709, which have significantly narrower gamuts than those used in professional workflows. Professional VFX pipelines typically work in 16-bit or 32-bit float to preserve maximum image quality and provide the necessary latitude for complex compositing operations. However, integrating AI-generated content into professional color pipelines has become more feasible through the Academy Color Encoding System (ACES). By converting 8-bit AI outputs from their native sRGB/Rec.709 space into ACES CG (AP1) color space early in the pipeline, we can work with them in a scene-referred linear color space alongside traditional CGI and live action footage. Additionally, I'm optimistic about emerging research in AI upsampling techniques. Just as we've seen remarkable progress in spatial resolution upscaling, I anticipate we'll soon see AI models capable of intelligently expanding 8-bit content to 16-bit color depth, potentially inferring subtle tonal variations and recovering lost detail. These developments would further bridge the gap between current AI tools and professional VFX requirements, making AI-assisted workflows more viable for high-end production.

💡 Final Thoughts

The future of VFX will be shaped by thoughtful collaboration between artists, technologists, and AI systems. By carefully integrating these tools while preserving human creativity and storytelling, we can expand the boundaries of what's possible in visual effects while maintaining the artistic integrity that gives our work meaning.