Importantly, if there are any issues with the automated detection process for detecting skin tone or facial features, you can manually override the effect by feeding it an alpha channel to manually inform where the face is or tweaking the settings in the OpenFX menu to inform the software what skin tone looks like. When you first apply the Face Refinement ResolveFX and start its analysis, the tool tracks an outline of the talent’s face, allowing you to independently adjust facial features, which have been arranged in convenient sections. This nifty tool makes fast work of touching up skin, removing eye bags, enhancing and sharpening eyes, and even allowing a subtle relighting of the subject’s face (when appropriate). One of my favorite AI-driven effects within DaVinci Resolve has to be the Face Refinement.

With the release of DaVinci Resolve 17 Studio, Blackmagic Design took this several steps further with multiple Neural Engine-powered features, such as Magic Mask, Scene Cut Detection, Smart Deinterlacing, Smart Object Removal, and Smart Reframe. It was their first step into providing AI/machine learning tools within the application, and included automated effects features like Face Refinement, Auto Color, and Optical Flow Speed Warp. In my daily work as a colorist and finishing artist, I’ve started regularly reaching for these tools in DaVinci Resolve, and thought I’d share five ways that you might introduce them into your own workflow (as well as a few examples of when they fall flat.) What smart tools are available in DaVinci Resolve?īlackmagic Design started their AI journey with Neural Engine, introduced with DaVinci Resolve 16 Studio in 2019. And this trend shows no signs of slowing down.

Software developers like Adobe, Blackmagic Design, and FilmLight have all been quick to add features that rely on these emerging technologies. It’s clear that machine learning (ML) and artificial intelligence (AI) have found a natural home in post-production workflows.

Davinci resolve editing