# ScanNet/ScanNet

Repository: https://github.com/ScanNet/ScanNet
Canonical: https://ross.abutalabs.com/products/scannet
Homepage: http://www.scan-net.org/
Language: C
License: NOASSERTION
License Family: other
Topics: rgbd, 3d-reconstruction, computer-vision, computer-graphics, deep-learning
Last push: 2025-11-03T12:14:27+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 50, release rhythm 35, longevity 100
- inputs: {"age_days": 3490, "days_push": 303, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2331, forks 374 (observed 2026-08-28T04:06:37.725029+00:00)

## What it is
ScanNet is a large RGB-D video dataset with 2.5 million views across 1500+ indoor scans, annotated with 3D camera poses, surface reconstructions, and instance-level semantic segmentations. The repository also includes a C++/Python toolkit for parsing the sensor streams and data files.

## Use cases
- train 3d scene understanding models on rgb-d data
- semantic segmentation of indoor 3d scans
- benchmark 3d object detection and voxel labeling
- evaluate rgb-d slam and camera pose estimation
- get annotated 3d meshes of indoor scenes for deep learning
- cad model retrieval research dataset

## When to choose
- you need large-scale annotated RGB-D indoor scene data for 3D vision research
- you want a standard benchmark for 3D semantic segmentation or object detection
- you need camera poses plus reconstructed meshes together

## When to avoid
- you need outdoor or LiDAR data
- you cannot agree to the ScanNet Terms of Use or use a non-institutional email
- you need a ready-to-use model rather than a dataset

## Facets
- artifact type: dataset
- maturity: stable
- function: computer-vision, machine-learning, image-processing, data-science
- domain: computer-vision, deep-learning, graphics, artificial-intelligence
- platform: cpp, python, cross-platform
- tags: rgbd, 3d-reconstruction, semantic-segmentation, benchmark, indoor-scenes, 3d-scene-understanding, meshes, camera-pose, linux

## Member repositories
- ScanNet/ScanNet (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:37.725029+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:37:58.587560+00:00, confidence not recorded.
  - readme: https://github.com/ScanNet/ScanNet (fetched 2026-08-28T04:06:37.725029+00:00, sha b87ff29fc949)
  - homepage: http://www.scan-net.org/ (fetched 2026-08-29T10:18:23.172835+00:00, sha b26e66455a84)
  - site_page: http://www.scan-net.org/changelog (fetched 2026-08-29T10:18:23.175290+00:00, sha 69d8f2c6528d)
- Data as of 2026-08-30T08:39:29.467469+00:00.