facebookresearch/consistent_depth

Health v2 · maintenance only

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1634 stars · 227 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A research library from Facebook AI Research implementing Consistent Video Depth Estimation (SIGGRAPH 2020). It reconstructs dense, flicker-free, geometrically consistent depth maps for all pixels in monocular video, such as hand-held cell phone footage, by fine-tuning a single-image depth network against structure-from-motion constraints.

Use cases

• estimate depth maps from monocular video
• make flicker-free depth for handheld phone video
• reconstruct scenes from a single camera video
• create video visual effects using depth
• convert 2D video to 3D-aware content
• run depth estimation on a Colab notebook

When to choose

• you need temporally consistent depth for a specific monocular clip and can afford per-video optimization
• you have an NVIDIA GPU and can install COLMAP and FFmpeg
• you want a research-grade reference implementation of the SIGGRAPH 2020 paper

When to avoid

• you need real-time depth estimation
• you want a plug-and-play pretrained model without per-video fine-tuning
• you have no GPU or cannot set up COLMAP dependencies
• you need actively maintained production software

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing video-processing computer-vision machine-learning deep-learning python depth-estimation monocular-video structure-from-motion siggraph-2020 research-code 3d-reconstruction video linux gpu

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markdown · JSON · MCP: product_card(name="facebookresearch/consistent_depth")