facebookresearch/vggsfm

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1421 stars · 116 forks observed · 2026-08-28

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

VGGSfM is a deep learning-based Structure from Motion pipeline from Meta AI and Oxford VGG that recovers camera poses and 3D point clouds from image collections. It is a Python/PyTorch research library with pretrained checkpoints, supporting video sequences, dynamic object masking, dense depth prediction, and Gaussian splatting export.

Use cases

• reconstruct 3d scenes from a set of photos
• estimate camera poses from images
• generate point clouds from video frames
• recover camera trajectory from a video
• prepare camera poses for gaussian splatting
• filter moving objects in sfm reconstruction
• export dense depth maps from images

When to choose

• you need deep-learning-based SfM that handles many frames or dynamic scenes
• you want camera pose estimation for downstream 3D tasks like Gaussian splatting
• you want a research-grade pipeline with pretrained models and a demo

When to avoid

• you need a lightweight classical SfM tool like COLMAP without GPU/deep learning dependencies
• you need a production system with long-term support guarantees
• you cannot run CUDA/PyTorch on your machine

Facets

library · maturity active

machine-learning computer-vision image-processing deep-learning computer-vision machine-learning deep-learning graphics python structure-from-motion camera-pose-estimation 3d-reconstruction point-cloud pytorch research gpu linux macos

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