It Took Me 30 Years to Solve This VFX Problem – Green Screen Problem [video] (youtube.com)

In an earlier video they made a couple years back about Disney's sodium vapor technique Paul Debevec suggested he was considering creating a dataset using a similar premise: filming enough perfectly masked references to be able to train models to achieve better keying. So it was interesting seeing Corridor tackle this by instead using synthetic data.

From ~04:10 till 05:00 they talk about sodium-vapor lights and how Disney has the exclusive rights to use it. From what I read the knowledge on how to make them is a trade secret, so it's not patented. Seems weird that it would be hard to recreate something from the 1950's.

I also wonder how many hours were wasted by people who had to use inferior technology because Disney kept it secret. Cutting out animals and objects from the background 1 frame at a time seems so mindnumbingly boring.

As far as alternatives, I wonder if anyone has tried a screen that cycles through colors in a known sequence. Using this modulating-color screen, it might actually be easier to separate the subject because you get around the "green shirt over green screen" problem. You might even be able to use a time sampling to correct the light cast on the subject from the screen as you would have a full spectrum of response.

I could also imagine using polarized light as the backdrop as well.

It’s fascinating to see the bridge between academic research and industry application here. While Image Matting is a massive research area in Computer Vision, academia often focuses on solving perfect 'benchmarks.' Corridor Crew effectively took that foundational research, like neural unmixing and synthetic training, and adapted it to solve the 'messy' reality of production, like tracking markers and motion blur. It’s a great example of using open-source deep learning resources to build a tool that prioritized workflow over just a high accuracy score.