Jumpat/SegmentAnythingin3D

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1030 stars · 64 forks observed · 2026-08-28

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

SA3D is a research framework that lifts 2D Segment Anything (SAM) masks into 3D segmentation of objects within a NeRF or 3D Gaussian Splatting scene from a single prompted view. It includes a NeRF-based implementation, a nerfstudio variant, and a 3D-GS segmentation dataset.

Use cases

• segment an object in 3d from a nerf scene
• get 3d masks from segment anything prompts
• extract a 3d model of a target object from a radiance field
• segment anything in 3d with gaussian splatting
• research on 3d scene perception and segmentation
• one-shot 3d segmentation from a single view

When to choose

• you already have a NeRF or 3D-GS representation of a scene and need object-level 3D segmentation
• you want a published, peer-reviewed method (NeurIPS 2023 / IJCV 2025) for SAM-based 3D lifting
• you need a benchmark dataset for 3D Gaussian Splatting segmentation

When to avoid

• you need segmentation of raw images or videos without an existing NeRF/3D-GS model
• you need a production-ready, optimized pipeline rather than research code
• your project does not involve neural radiance fields or 3D scenes

Facets

library · maturity active

computer-vision image-processing machine-learning deep-learning computer-vision deep-learning machine-learning artificial-intelligence python 3d-segmentation nerf segment-anything gaussian-splatting research neurips linux gpu

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markdown · JSON · MCP: product_card(name="Jumpat/SegmentAnythingin3D")