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Through the Depths of Time
 

Film  VR Experience  Volumetric Media

 


Tools: ComfyUI  Luma AI  Postshot  Unreal Engine  Nuke

Through the Depths of Time is a film and a virtual reality experience that moves through moments of human history as if they were memories suspended in space. Rather than presenting history as a fixed sequence of events, the work reimagines it as something fluid, unstable, and spatial, something that can be entered and experienced from within.

The work begins with AI-generated imagery, which I then transform into volumetric environments using Gaussian splatting through a custom reconstruction process. These environments are later animated in real time in Unreal Engine, where each scene shifts, dissolves, and reforms through particles, light, and motion.

I approach AI as a tool that opens up new possibilities for developing my own visual language. I am not a traditional 3D modeler, but I have always wanted to create custom environments, so I became interested in whether this technology could help me do that. Through this process, I started to treat images not as something fixed, but as something that can be rebuilt, transformed, and experienced as space.

I use Gaussian splatting and reconstruction not to scan reality, but to construct scenes that never existed, using synthetic multi-view imagery generated from AI images. This shift from capturing reality to constructing it became central to the project. Because the scenes are built as spatial environments rather than flat images, I was able to extend the work into VR, allowing the viewer not only to watch the film, but to enter the scenes and experience them from within.

Selected Scenes

• The First Fire • 
• Navigation •
• Penicillin Discovery •
• Industrial Revolution •

Synthetic Cinema 

AI Generation • Compositing • Controlled Workflows
Synthetic Cinema explores AI-driven image generation through structured prompting, controlled workflows, and compositing; presenting a curated set of cinematic experiments that examine control, consistency, and performance in generative image-making.

Selection of generated sequences and composited shots
Cinematic Results 
Character & Voice Performance
Exploring character behavior, speech, and timing in generative systems

About

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Marzena Milowska is an international, multidisciplinary artist working across film, visual effects, and emerging technologies. She holds a BA in Digital Animation from the University of West London, completed professional training in Digital Compositing for Film and VFX at Escape Studios in London, and earned an MFA in Computer Arts (STEM), the terminal degree in the field, from the School of Visual Arts.

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Her research explores AI-driven volumetric media, including Neural Radiance Fields (NeRFs), Gaussian Splatting, and real-time systems in Unreal Engine. Drawing on experience in VFX studios such as MPC and Prime Focus (now DNEG), contributing to major film productions including Harry Potter and Star Wars, she brings a cinematic sensibility to computational practice.

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A Fellow of the Royal Society of Arts (FRSA), elected for her contributions to art and innovation, and an award-winning filmmaker of the documentary Jinxsie, Marzena creates hybrid works across AI, VFX, and immersive media, expanding contemporary image-making beyond traditional disciplinary boundaries.

SYNTHETIC CINEMA
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