The results of DaVinci Resolve’s Detect Scene Cuts tool. While it’s not as sexy as some of the other Neural Engine-powered features like Magic Mask or Face Refinement, Detect Scene Cuts has become a daily-use tool for me. I can’t emphasize how useful this feature is for boosting workflow efficiency. If you need to add or remove a cut, you can easily do so using Resolve’s native tools after the AI-driven process finishes. Simply select the clip you’d like to detect cuts within on the timeline, go to the Timeline menu, and select Detect Scene Cuts.Ī dialogue box appears while Resolve processes and once complete, you’ll see these new cuts on your timeline. Luckily, the new Detect Scene Cuts feature is fast, easy, and intuitive for anyone familiar with Resolve’s non-linear editing environment. Honestly, it wasn’t much better than going through with a razor tool and slicing, which I often found myself doing as a faster alternative, especially if the timeline includes transitions. The previous Scene Cut Detection tool-available only on the media page prior to import-required a lot of hand-holding or a perfectly prepared edit decision list (EDL) provided from editorial, which I don’t always receive. Detect Scene CutsĭaVinci Resolve may have had a Scene Detect Workflow previously, but it’s nothing like the smarter Neural Engine powered tool introduced with Resolve 17. This occurs when Face Refinement uses tracking data from the previous shot after being copied from another shot. Unfortunately, the drawback of this effect is that the “analysis” process must be run on every single clip manually, which can dramatically slow down your workflow and-potentially worse-can easily be forgotten, which can result in the infamous “floating eyes” output. Tweaking the Face Refinement settings after analysis. The critically important aspect for me is access to individual effect controls, which offers quick and easy adjustments that ensure consistency between shots without too much fiddling on my part. 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.
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