That ugly green halo around hair every time someone gets cut out of a green screen is a 30-year-old math problem that traditional keyers can't solve, and a YouTube studio in LA just open-sourced the fix.
Edges are hard for one reason. A pixel at the boundary of your subject covers maybe 30% skin and 70% green screen. The camera averages them: recorded RGB is literally 0.3 * skin 0.7 * green. Same physics for motion blur, out-of-focus hair, glass, smoke, fabric. Every translucent pixel is a mix of subject light and background light.
Primatte, Keylight, Ultimatte (the workhorse keyers behind basically every Hollywood green screen shot since the 90s) estimate which pixels to keep with a binary mask. Modern "AI roto" tools do the same thing with neural networks predicting the mask. Both throw away the mixed pixel. That's why every cutout you've ever seen has either harsh edges or a green tint in the hair.
CorridorKey predicts the actual unmixed foreground RGB plus a linear alpha for every pixel. Given observed pixel = alpha * foreground (1 - alpha) * background, the network solves for foreground and alpha directly. That's what Porter-Duff compositing math has wanted since 1984. The industry has been duct-taping around the missing solver with manual roto for forty years.
Outputs are 16/32-bit EXR. Plugs into Nuke, Fusion, and DaVinci Resolve via community ports that appeared within weeks of release. Trained on synthetic rendered data, so dataset cost is essentially zero. Niko Pueringer (one of the two Corridor founders) wrote it. This is the level of tool top VFX shops typically keep proprietary. Corridor put it on GitHub.
The gating constraint flipped from algorithm to VRAM. Inference at 2048x2048 needs about 23GB. That's a $2K consumer GPU. A shot that takes a roto artist a full day now runs in under a second on the same hardware kids use to play Cyberpunk.
Green screen keying, solved at the pixel level.
Corridor's neural keyer unmixes edges into true foreground color and linear alpha, EXR out.