Notes by ReelStack · AI-assistedUpdated 6 October 2026

How to Create a Depth Map Using AI + FREE Tool Download

Shows AI filmmakers how to extract depth maps to retain precise motion and composition consistency when transforming live-action or graybox footage into stylized scenes.

Video thumbnail: How to Create a Depth Map Using AI + FREE Tool Download
Original YouTube video

Curious Refuge

Published

Watch the original video ↗

What this lesson covers

Curious Refuge demonstrates how to create depth maps from reference footage using fal.ai or a free local Mac application. The video then shows how to input the resulting depth map into Magnific with Seedance 2.5 to guide motion and environment changes.

Key takeaways from the creator

AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.

  1. 0:16 ↗

    Depth maps serve as black-and-white representations of spatial depth that help AI tools adhere accurately to original reference footage during environment transformations.

  2. 0:41 ↗

    Depth maps can be generated in cloud aggregators like fal.ai using models like VDA Large in roughly 60 seconds.

  3. 1:27 ↗

    Local depth map generation can be executed for free on macOS via packaged open-source command scripts.

  4. 2:17 ↗

    In Magnific, a depth map can be combined with Seedance 2.5, a keyframe style image, and original reference footage to control motion and facial likeness.

Workflow outlined in the video

  1. Upload raw or graybox reference footage to an online aggregator such as fal.ai.
  2. Select the VDA Large model (or Depth Anything) and render the depth map video.
  3. Alternatively, run a local macOS depth-mapping script and drag and drop the reference footage into the tool.
  4. Open Magnific and select Seedance 2.5 as the video generation model.
  5. Upload the generated depth map video, a target style starting frame, and the original video reference.
  6. Craft a prompt specifying image one as the starting frame, the depth video as motion reference, and detailing the desired scene output before rendering.

Before you use this workflow

These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.

ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.

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How to interpret the numbers

9,552 views captured 6 October 2026. ReelStack recommendation score: 47/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.

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  • 45% performance: 0.44× views vs 8 other channel videos observed at a similar age. View-evidence factor 91% (views / (views + 1,000))
  • 25% freshness: 84/100 with a 14-day half-life
  • 20% momentum: 1303 views/day vs 1247 channel baseline (8 comparable uploads), with the same view-evidence factor
  • 10% engagement: 40/100; likes + 4× comments, smoothed with a 500-view neutral prior

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