# HengyiWang/spann3r

[3DV'25 Award Candidate] 3D Reconstruction with Spatial Memory

Repository: https://github.com/HengyiWang/spann3r
Canonical: https://ross.abutalabs.com/products/spann3r
Homepage: https://hengyiwang.github.io/projects/spanner
Language: Python
License: NOASSERTION
License Family: other
Topics: 3d-reconstruction
Last push: 2025-02-25T01:13:37+00:00

## Health v2 (maintenance only)
Score: 26/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 8, release rhythm 35, longevity 51
- inputs: {"age_days": 721, "days_push": 555, "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 1141, forks 52 (observed 2026-08-28T04:03:44.510916+00:00)

## What it is
Spann3R is a transformer-based model for dense 3D reconstruction from ordered or unordered image collections, built on the DUSt3R paradigm. It uses an external spatial memory to regress per-image pointmaps in a global coordinate system without test-time optimization or camera pose estimation.

## Use cases
- reconstruct 3d scenes from image sequences
- dense 3d reconstruction from uncalibrated photos
- incremental 3d mapping without camera pose estimation
- real-time 3d reconstruction from video frames
- reconstruct dynamic scenes from images
- export 3d reconstruction to nerfstudio

## When to choose
- you need pointmap-based 3D reconstruction from images without SfM preprocessing
- you want incremental reconstruction in a global coordinate frame with a single forward pass
- you need to handle both static and dynamic scenes
- you want to feed reconstructions into Nerfstudio

## When to avoid
- you need a production-ready, licensed product (license is non-standard/unclear)
- you lack a CUDA-capable GPU, since it requires PyTorch with CUDA and compiled kernels
- you need metrically accurate, survey-grade 3D reconstruction
- you need a lightweight CPU-only pipeline

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, computer-vision, image-processing
- domain: computer-vision, machine-learning, deep-learning, artificial-intelligence
- platform: python
- tags: 3d-reconstruction, pointmap, spatial-memory, transformer, dust3r, nerfstudio, research-code, pytorch, linux, gpu

## Member repositories
- HengyiWang/spann3r (main) score 26

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:44.510916+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 2026-08-30T06:35:21.982691+00:00, confidence not recorded.
  - readme: https://github.com/HengyiWang/spann3r (fetched 2026-08-28T04:03:44.510916+00:00, sha 81e9c72d3afa)
  - homepage: https://hengyiwang.github.io/projects/spanner (fetched 2026-08-29T12:40:21.810476+00:00, sha 072fcad7d9f9)
- Data as of 2026-08-30T08:39:29.467469+00:00.