Every Platform Wants a Different Frame
You have one great piece of video. Maybe it is a keynote talk, a product walkthrough, or an interview you spent real money to light and shoot properly. Now you need to put it out into the world. TikTok wants 9:16. Instagram feed wants 4:5. LinkedIn performs best with 1:1. YouTube Shorts needs 9:16 again but at different metadata specs. And your website embed still looks best at 16:9. That is five different aspect ratios from a single source file, and every single one needs the subject framed correctly or the content falls flat.
This is not a hypothetical problem for a handful of power users. It is the daily reality for anyone publishing video across more than one platform. The algorithms on TikTok, Instagram, and YouTube all penalize content that does not fill the viewport natively. A letterboxed 16:9 clip inside a 9:16 frame screams laziness to viewers, and the engagement numbers reflect it immediately. Every platform has trained its audience to expect full-bleed, perfectly framed video, and anything less gets scrolled past without a second thought.
The Old Way: Duplicate Timelines, Manual Exports
In Premiere Pro, the standard approach is to create a separate sequence for each output ratio. You duplicate your timeline, change the sequence settings to 1080x1920 for vertical, then manually reposition and scale your footage so the subject stays in frame. Repeat for 4:5. Repeat again for 1:1. Each sequence needs its own position keyframes because the crop window is different, and a framing that works for 9:16 almost never works for 1:1 without adjustment. For a single two-minute clip, you are looking at three to five additional timelines and thirty minutes of tedious repositioning work.
CapCut and Canva try to simplify this with auto-reframe features, but they still force you to export one ratio at a time. You run the auto-reframe, review it, fix the spots where it drifted, export, then start the entire process again for the next ratio. There is no way to queue up multiple aspect ratios and walk away. Descript has a similar limitation. You can change the canvas size, but each ratio is a separate export job that you have to babysit. The tooling treats multi-ratio delivery as an afterthought rather than a core workflow, and creators pay for it in hours every single week.
The cloud-based tools add another layer of friction on top of the manual work. Uploading raw 4K footage to Kapwing or any browser-based editor takes real time on real bandwidth, and you are trusting a third party with unreleased content. For anyone working under NDA or handling client footage, that is a non-starter. The entire pipeline: upload, wait, process, download, repeat for each ratio, is built around assumptions that do not hold when you need to move fast and keep your files local.
How Batch Export Works in FaceStabilizer
FaceStabilizer collapses the entire multi-ratio export into a single linear workflow. You import your video, click Select Face, and the app runs face detection across the footage. It draws bounding boxes around every detected face and lets you click the one you want to track. Hit Start Tracking, and the AI locks onto that face frame by frame across the entire clip. The tracking data is computed once and reused for every ratio you export. No re-tracking, no redundant processing.
Here is where it gets good. After tracking, you select your output ratios. This is not a single dropdown. It is a multi-select. Check 9:16, check 4:5, check 1:1, check 16:9, check 3:4. Pick two or pick all five. Then hit Generate Preview to see how each ratio frames your subject. Once you are satisfied, click Export All and FaceStabilizer renders every selected ratio sequentially from the same tracking data. One click, all formats, no babysitting. The app names each output file by its ratio so you can drag and drop straight into your publishing workflow.
The tracking and stabilization settings carry across all exports, but you can adjust stabilization mode after tracking without re-running the face detection. If you decide Smooth mode looks better than Balanced after previewing, just switch it and regenerate. The face tracking data stays intact. This means you can experiment freely with how the crop moves without waiting for the AI to re-analyze your footage every time. FaceStabilizer auto-generates a lightweight preview so scrubbing stays responsive even on longer files.
Compare Mode: Preview All Ratios Side by Side
Selecting multiple ratios unlocks a feature that no other reframing tool offers at the desktop level: the Compare button. Click it and FaceStabilizer renders a side-by-side preview of every selected ratio simultaneously, playing in sync. You can see exactly how 9:16, 4:5, and 1:1 frame the same moment in your video, all at once, without switching between tabs or toggling between separate preview windows. It is the fastest way to catch framing issues before you commit to a full export.
Compare mode is particularly valuable when your subject moves around the frame. A composition that looks perfect in 1:1 might clip the top of someone's head in 9:16, or a 4:5 crop might leave too much dead space above the subject during a seated interview. Seeing all ratios simultaneously lets you make one stabilization adjustment that works across the board rather than optimizing for each ratio individually. It turns what used to be a guess-and-check loop into a single visual decision.
This is the kind of feature that saves you from discovering a bad crop after you have already exported, uploaded, and scheduled a post. Catching it in the preview costs you five seconds. Catching it after publication costs you reach, engagement, and the time to re-export and re-upload. Compare mode exists because we got tired of that exact cycle ourselves, and we built the tool we wished we had.
Quality Settings: Resolution and Upscaling
Batch export is only useful if the output quality holds up. FaceStabilizer encodes all exports in an industry-standard format accepted by every major platform and editing application. Audio quality is preserved, so you never lose fidelity in the reframing process. The encoding quality depends on your tier, and the difference is significant.
Pro exports at near-lossless quality. You would struggle to tell the difference between the export and the source file even on a calibrated monitor. Pro also supports resolutions up to full 4K, so if you are working with high-resolution source footage, your exports maintain that quality across every ratio. For creators publishing to platforms that support 4K (YouTube, Instagram, TikTok), this is the quality ceiling that keeps your content looking sharp even after the platform applies its own compression.
The free tier exports at up to 720p with a 30-second clip limit. That is more than enough to test the workflow end to end, see how the face tracking performs on your footage, and decide if the tool fits your process. For Pro users who want to push quality even further, FaceStabilizer includes built-in AI upscaling. This is especially powerful when you are cropping a 1080p landscape clip down to 9:16, which effectively reduces your working resolution. The upscaler recovers detail and sharpness, giving you an output that looks like it was shot at a higher resolution than it actually was.
One Video In, Five Formats Out. That Is the Workflow
The entire point of FaceStabilizer is to make multi-platform video delivery feel effortless instead of exhausting. Import one video. Select one face. Track once. Pick your ratios. Export all. Five files land in your output folder, each perfectly framed, each ready to upload directly to its target platform. No duplicate timelines in Premiere. No five separate export jobs in CapCut. No uploading your raw footage to someone else's cloud. Everything happens on your machine, privately and fast.
This workflow scales whether you are a solo creator cutting one video a week or a production team processing dozens of client deliverables. The time savings compound quickly: what used to take an hour of manual cropping and multiple export passes now takes a few minutes of setup and a single batch render. And because the processing is entirely local (macOS and Windows, no internet required). You are never waiting on upload speeds or server queues. Your hardware does the work, and your files never leave your drive.
We built FaceStabilizer because we were tired of the friction between shooting great footage and actually getting it onto every platform where it needed to live. One video in, five formats out. That is not a tagline. It is literally the workflow. Try it on your next piece of content and feel the difference when multi-platform delivery stops being a chore and starts being a single click.