Description
In this episode of the fxpodcast, we speak with David Schneider from Union VFX about one of the most interesting new production workflows to emerge around Gaussian splatting: using splats not simply as a visualisation technique, but as a practical crowd solution for feature film production.
Union VFX has been developing the approach in partnership with Clear Angle Studios, building on Clear Angle’s new Volumetric Capture Rig, or VCR. The rig uses 40 synchronised machine-learning cameras in a half-dome configuration, with integrated LED lighting, allowing performers to be captured under highly controlled, neutral lighting conditions. From those captures, Union can generate animated 4D Gaussian splats that retain a strong sense of photographic realism while being deployable inside a conventional VFX pipeline.
The key breakthrough is not just capture quality, but control. Gaussian splats are often admired for their realism, but they also present major production challenges, especially around temporal stability, segmentation, mattes, and relighting. In the podcast, Schneider explains how Union and Clear Angle have built a pipeline that allows the splats to be relit inside CG scenes using production lighting, cast and receive shadows, and be treated by compositors much more like traditional CG assets.
For crowd work, this is especially significant. Traditional CG crowds require modelling, rigging, animation, agent systems, and extensive variation work. Card-based crowds can be efficient, but they quickly fall apart when lighting or camera movement changes. Union’s approach sits somewhere new: captured real human performances, processed as splats, instanced into large-scale environments, and then relit and art-directed shot by shot.
00:00 Intro
06:06 Solution to Lighting Problems
08:21 Image Segmentation
09:10 4D Capture
13:10 Bike Rider Test
15:20 Crowd Size
16:46 Crowd Distance to Camera
18:27 Where This Workflow is Heading
20:19 View-Dependant Lighting Situation
22:00 Feedback From the Industry
23:29 Temporal Consistency
25:27 Directability
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